Patent Publication Number: US-11391840-B2

Title: Distance-measuring apparatus, mobile object, distance-measuring method, and distance measuring system

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This patent application is based on and claims priority pursuant to 35 U.S.C. § 119(a) to Japanese Patent Application No. 2018-120207, filed on Jun. 25, 2018, in the Japan Patent Office, the entire disclosure of which is hereby incorporated by reference herein. 
     BACKGROUND 
     Technical Field 
     Embodiments of the present disclosure relate to a distance-measuring apparatus, a mobile object, a distance-measuring method, and a distance-measuring system. 
     Background Art 
     As an algorithm for calculating a disparity for stereo cameras, block matching in which feature points are used is known in the art. In the block matching, a feature point is searched for while shifting a right or left image, and the amount of shift is regarded as a disparity. Then, a cost is calculated on a disparity-by-disparity basis, and a disparity that minimizes the cost in the searching disparity space is detected. Finally, in the block matching, the distance to each pixel is calculated according to an equation “Z=BF/d” indicating the relation between a disparity d and a distance Z, where B denotes a base-line length and F denotes a focal length. The semi-global matching (SGM) propagation method where a disparity value is precisely derived even from an object with a little texture is also known in the art. 
     However, it is difficult to secure the distance resolution at a remote site in regard to the distance that is calculated from a disparity using such an algorithm as above for calculating a disparity, and the variations in value of distance measurement (or the distribution of the values of distance measurement) tend to increase. 
     For example, in the on-vehicle industry as typified by automatic driving industry, improvement in performance of distance measuring at a remote point is sought after. In order to achieve such improvement, correction of the distance that is calculated from a disparity using calculator algorithm as above for calculating a disparity, using the distance information obtained by using light detection and ranging (LiDAR) or laser imaging detection and ranging (LiDAR) where the spatial resolution is low but the range resolution is high, is under study. In the LiDAR, the distance to an object is calculated based on the length of time it takes from a point in time when a laser beam is emitted to an object until a point in time when a reflected signal returns from the object. For example, methods in which a peak of the reflected signals is detected are known in the art as a method of specifying a reflected signal from an object based on the reflected signals that are obtained in chronological order. 
     Conventionally, an attempt to combine the measurement result obtained by a LiDAR device where the spatial resolution is low but the range resolution is high with the measurement result of a stereo camera where the spatial resolution is high but the distance resolution is low at a remote point is known in the art (see, for example, JP-2015-143676-A). Such a combination may be referred to as a fusion. JP-2015-143676-A discloses a disparity computation system that generates a disparity image. In such a disparity computation system, the distance information obtained by using the LiDAR is associated with each one of the pixels of a captured image, and a value based on the distance information associated with each one of the pixels of the captured image is used to compute the disparity of each one of the pixels of the captured image. Due to such a fusion as above, for example, output of a three-dimensional high-resolution distance-measuring result, a narrow distribution of values of distance measurement, highly-precise detection of a surface of discontinuity, downsizing, and an improvement in environmental robustness may be achieved. 
     SUMMARY 
     Embodiments of the present disclosure described herein provide a distance-measuring apparatus, a mobile object, a distance-measuring method, and a distance-measuring system. The distance-measuring apparatus and the distance-measuring method include performing matching for a plurality of images obtained by a plurality of imaging devices to convert the plurality of images into first distance information on a pixel-by-pixel basis, emitting a laser beam where at least one of a laser-beam resolution in a horizontal direction and a laser-beam resolution in a vertical direction exceeds two degrees, obtaining a reflected signal obtained when the laser beam is reflected by an object, detecting a peak that corresponds to reflection from the object from the reflected signal, calculating second distance information based on a length of time taken to observe the peak after the laser beam is emitted in the emitting, and integrating the first distance information and the second distance information with each other. The mobile object includes the distance-measuring apparatus. The distance-measuring system includes the distance-measuring apparatus. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       A more complete appreciation of embodiments and the many attendant advantages thereof will be readily obtained as the same becomes better understood by reference to the following detailed description when considered in connection with the accompanying drawings. 
         FIG. 1  is a diagram illustrating the spatial resolution and the distance resolution of a stereo camera, a LiDAR device, and a principle fusion in comparison to each other. 
         FIG. 2A  and  FIG. 2B  are diagrams each illustrating the relation between the distance resolution and the spatial resolution of a stereo camera and a LiDAR device depending on varying distance. 
         FIG. 3  is a diagram illustrating three objects in an irradiation field of low laser-beam resolution, according to an embodiment of the present disclosure. 
         FIG. 4  is a schematic diagram illustrating a reflected signal obtained when a laser beam is reflected by a plurality of objects, according to an embodiment of the present disclosure. 
         FIG. 5  is a diagram illustrating a distance-measuring apparatus provided for a car as an example of a mobile object, according to an embodiment of the present disclosure. 
         FIG. 6A  and  FIG. 6B  are diagrams each illustrating the irradiation field of the laser beams emitted by a LiDAR range finder, according to an embodiment of the present disclosure. 
         FIG. 7  is an external view of a distance-measuring apparatus installed in a vehicle in front of a rear-view mirror, according to an embodiment of the present disclosure. 
         FIG. 8  is a diagram illustrating a schematic configuration of a distance-measuring apparatus according to an embodiment of the present disclosure. 
         FIG. 9  is a diagram illustrating a hardware configuration of a distance-measuring apparatus according to an embodiment of the present disclosure. 
         FIG. 10A  and  FIG. 10B  are diagrams illustrating a difference in the signal level received at a close point and a remote point, according to an embodiment of the present disclosure. 
         FIG. 11A  and  FIG. 11B  are diagrams each illustrating a scene in which a laser beam is emitted, according to an embodiment of the present disclosure. 
         FIG. 12A ,  FIG. 12B , and  FIG. 12C  are diagrams each illustrating an image of irradiation when a laser beam of low laser-beam resolution is emitted, according to an embodiment of the present disclosure. 
         FIG. 13A  and  FIG. 13B  are diagrams each illustrating a configuration of the irradiation unit of a LiDAR range finder in which a low laser-beam resolution as illustrated in  FIG. 12A ,  FIG. 12B , and  FIG. 12C  is implemented, according to an embodiment of the present disclosure. 
         FIG. 14  is a diagram illustrating a configuration of a distance-measuring apparatus according to an embodiment of the present disclosure. 
         FIG. 15A  and  FIG. 15B  are diagrams illustrating block matching according to an embodiment of the present disclosure. 
         FIG. 16  is a graph in which a cost value is indicated for each degree of the amount of shift, according to an embodiment of the present disclosure. 
         FIG. 17  is a schematic view of how a synthesis cost is derived according to an embodiment of the present disclosure. 
         FIG. 18  is a graph of synthesis-cost curve indicating the synthesis cost for each one of the disparity values, according to an embodiment of the present disclosure. 
         FIG. 19  is a diagram illustrating the synthesis cost of metric space obtained by converting the synthesis cost of disparity space, according to an embodiment of the present disclosure. 
         FIG. 20A ,  FIG. 20B , and  FIG. 20C  are diagrams illustrating a method of calculating a LiDAR cost, according to an embodiment of the present disclosure. 
         FIG. 21  is a diagram illustrating the distance information calculated and obtained by a distance calculator, according to an embodiment of the present disclosure. 
         FIG. 22A ,  FIG. 22B , and  FIG. 22C  are schematic diagrams of a fusion between synthesis costs and LiDAR costs, according to an embodiment of the present disclosure. 
         FIG. 23  is a diagram illustrating pixel replacement according to the present embodiment. 
         FIG. 24  is a flowchart of how a fusion is performed based on a cost, according to an embodiment of the present disclosure. 
         FIG. 25  is a flowchart of how a fusion is performed as the distance to each pixel obtained by performing block matching is replaced with the distance data that is calculated based on the reflected signal, according to an embodiment of the present disclosure. 
         FIG. 26  is a flowchart of how a fusion is performed as the distance to each pixel obtained by performing block matching is replaced with the distance data that is calculated based on the reflected signal, according to an embodiment of the present disclosure. 
         FIG. 27A  and  FIG. 27B  are diagrams illustrating a scene in which the distance is measured by a distance-measuring apparatus and a distance image are illustrated, respectively, according to an embodiment of the present disclosure. 
     
    
    
     The accompanying drawings are intended to depict embodiments of the present disclosure and should not be interpreted to limit the scope thereof. The accompanying drawings are not to be considered as drawn to scale unless explicitly noted. 
     DETAILED DESCRIPTION 
     The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present disclosure. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “includes” and/or “including”, when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. 
     In describing example embodiments shown in the drawings, specific terminology is employed for the sake of clarity. However, the present disclosure is not intended to be limited to the specific terminology so selected and it is to be understood that each specific element includes all technical equivalents that have the same structure, operate in a similar manner, and achieve a similar result. 
     In the following description, illustrative embodiments will be described with reference to acts and symbolic representations of operations (e.g., in the form of flowcharts) that may be implemented as program modules or functional processes including routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types and may be implemented using existing hardware at existing network elements or control nodes. Such existing hardware may include one or more central processing units (CPUs), digital signal processors (DSPs), application-specific-integrated-circuits (ASICs), field programmable gate arrays (FPGAs), computers or the like. These terms in general may be collectively referred to as processors. 
     Unless specifically stated otherwise, or as is apparent from the discussion, terms such as “processing” or “computing” or “calculating” or “determining” or “displaying” or the like, refer to the action and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical, electronic quantities within the computer system&#39;s registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices. 
     A distance-measuring apparatus and a method of measuring distance using the distance-measuring apparatus according to an embodiment of the present disclosure are described below with reference to the accompanying drawings. 
     Fusion between Distance Measurement by Stereo Camera and Distance Measurement by LiDAR Device 
     Supplemental description of the fusion between the distance measurement performed by a stereo camera and the distance measurement performed by a light detection and ranging (LiDAR) device is given below. As a LiDAR device emits a laser beam, a LiDAR device may be referred to as a laser radar in the present embodiment. The light that is emitted by a laser radar (LiDAR device) is not limited to a laser beam, and the light source of a laser radar may be a light-emitting diode (LED). 
     Stereo cameras are characterized in that the spatial resolution is high but the distance resolution is low when at a remote point, and LiDAR devices are characterized in that the spatial resolution is low but the distance-measuring resolution is high. In a principle fusion where fusion is performed between the data obtained by a stereo camera and the data obtained by a LiDAR device at an early stage, a three-dimensional high-resolution distance-measuring image where the distance resolution is high even at a remote point and the spatial resolution is also high can be output. 
     As described above, the following problems of a stereo camera and a LiDAR device can be solved by a principle fusion. 
     1. Technical Problem of Stereo Camera 
     Accuracy of Distance Measurement: As the distance resolution gets low when at a remote point, the distance measurement and object detection are difficult when an object is at a remote point. 
     Targeting Capability: Erroneous matching tends to occur due to repeated patterns or poor texture, and a number of distance values with large variances tend to be detected. 
     Environmental Resistance: As almost no texture can be detected in the nighttime, it is difficult to calculate the distance. 
     Downsizing: In order to achieve downsizing, the base-line length needs to be shortened, and thus it is difficult to adopt, for example, a central processing unit (CPU) with high computation performance. If a program that require a lot of processes to be executed is installed in order to improve the precision of the processing, the processing time tends to get longer. When it is desired to shorten the processing time, for example, a smaller CPU with high computation performance needs to be adopted. 
     This leads to an increase in cost, which could be problematic. 
     2. Technical Problem of LiDAR Device 
     The distance resolution gets lower as the distance to an object is longer. 
     A method in which a threshold is set and a distance value is output is adopted. For this reason, a reflected signal whose value falls below the threshold is ignored even when a peak is actually detected. In particular, when a peak of a reflected signal is detected from a remote point, such a peak is not used even though a relevant signal is successfully obtained. 
     It is difficult to install a large number of light-emitting elements and light-receiving elements, and large light-emitting elements or large light-receiving elements cannot be installed. Due to this configuration, a reflected signal is extremely weak, and when the noise level of a reflected signal is relatively close to the magnitude of a peak of a reflected signal that corresponds to an object (when a signal-to-noise ratio (S/N ratio) of a signal is low), it is difficult to obtain accurate distance with a method in which a threshold is set. When a light-emitting element is multilayered or the LiDAR device is designed to have fine resolution, the manufacturing cost increases and the scanning of one plane cannot be done speedily, which could be disadvantageous. 
     The performance that is to be achieved by a principle fusion according to an embodiment of the present disclosure is described below. 
       FIG. 1  is a diagram illustrating the spatial resolution and the distance resolution of a stereo camera, a LiDAR device, and a principle fusion in comparison to each other. 
     As illustrated in  FIG. 1 , the spatial resolution of a stereo camera is high, and the spatial resolution of a LiDAR device is low when an object is at a remote point. However, when a principle fusion is adopted, high spatial resolution is achieved even when an object is at a remote point. The distance resolution of a stereo camera is low when an object is at a remote point, and the distance resolution of a LiDAR device is high regardless of the distance. However, when a principle fusion is adopted, high distance resolution is achieved even when an object is at a remote point. The performance that goes beyond the principle of measurement of a stereo camera and a LiDAR device can be obtained in such a principle fusion. 
     In the principle fusion according to the present embodiment, distance measuring can precisely be performed even when an object is at a remote point due to a synergetic effect of the performance of distance measuring by a stereo camera and a LiDAR device, and the reflection light (return light) may be weak. As the spatial resolution equivalent to that of the stereo camera can be achieved without increasing the spatial resolution of the LiDAR device, space separation may be achieved with an even lower laser-beam resolution. A low laser-beam resolution is described below with reference to  FIG. 2A  and  FIG. 2B . 
       FIG. 2A  and  FIG. 2B  are diagrams each illustrating the relation between the distance resolution and the spatial resolution of a stereo camera and a LiDAR device depending on varying distance. 
     Firstly,  FIG. 2A  illustrates a distance resolution. As illustrated in  FIG. 1 , the distance resolution of a stereo camera sharply deteriorates when an object is at a remote point. 
       FIG. 2B  is a diagram illustrating the spatial resolution. 
     As illustrated on the right side of  FIG. 2B , the spatial resolution of a stereo camera is high even when an object is at a remote point. By contrast, the spatial resolution of a LiDAR device deteriorates when an object is at a remote point. In  FIG. 2B , the spatial resolution of a laser beam is illustrated for each one of the laser-beam resolutions of 0.1, 0.2, 0.3, 0.4, 0.5, and 0.6 degrees. The laser-beam resolution indicates the angle of the directions in which one laser beam diverges. Laser beams diverge as the distance gets longer, and the spatial resolution at a remote point deteriorates as the laser-beam resolution is greater. 
     In  FIG. 2B , two lines are drawn at the spatial resolutions of 25 centimeters (cm) and 1.8 m, respectively. 25 cm corresponds to the size of a pedestrian, and 1.8 m corresponds to the size of a vehicle. For example, it is assumed that a vehicle at a distance of 200 m is captured by a laser beam. Under such circumstances, a laser beam whose laser-beam resolution is 0.5 degrees diverges to the width of less than 1.8 m at a point of 200 m distance ahead of the LiDAR device. Accordingly, when the laser-beam resolution of a laser beam is equal to or lower than 0.5 degrees, a laser beam hits a vehicle at a distance of 200 m. In other words, two or more vehicles at a distance of 200 m ahead of the LiDAR device can separately be detected even with a relatively low laser-beam resolution such as 0.5 degrees. 
     In the principle fusion according to the present embodiment, space separation can be performed with the spatial resolution of a stereo camera. Due to this configuration, the laser-beam resolution of the LiDAR may be low. For example, a high laser-beam resolution such as 0.1 to 0.2 degrees is not necessary for the principle fusion. When a low laser-beam resolution is acceptable, as will be described later in detail, space saving or cost reduction of a LiDAR distance-measuring apparatus can be achieved. 
     Example of Low Laser-Beam Resolution 
       FIG. 3  is a diagram illustrating three objects A to C in an irradiation field of low laser-beam resolution, according to the present embodiment. 
     For example, it is assumed that there are a plurality of objects A, B, and C and the relation among these objects in distance is as in “A&lt;B&lt;C.” Almost the entirety of the irradiation field  101  including the objects A to C therein can be irradiated with one laser beam of low laser-beam resolution. In other words, the irradiation field  101  is a range that can be irradiated at a time with one laser beam. 
       FIG. 4  is a schematic diagram illustrating a reflected signal obtained when a laser beam is reflected by objects A to C. 
     As illustrated in  FIG. 3 , the objects A to C are irradiated with a laser beam, and a reflected signal with multiple pulses is obtained. A reflected signal with multiple pulses refers to the phenomenon in which reflected signals return from a plurality of objects in response to one-time emission of a laser beam. As illustrated in  FIG. 4 , the three peaks  102  to  104  that correspond to the objects A to C are obtained for a reflected signal. 
     In  FIG. 4 , the distances to the objects A to C can be detected by comparing the obtained three peaks  102  to  104  with a threshold. However, the peaks  102  to  104  may substantially be buried in noise in a reflected signal obtained from a remote object or an object with a small reflection coefficient, and no peak may be obtained in a clear manner. However, in the present embodiment, the distance can be calculated using the data obtained by a stereo camera due to the principle fusion according to the present embodiment. Accordingly, the planes of the objects A to C each of which indicates the distance can be separated from each other. 
     Example Application to Distance-Measuring Apparatus 
     An example case in which a distance-measuring apparatus  100  is applied is described below with reference to  FIG. 5 . 
       FIG. 5  is a diagram illustrating the distance-measuring apparatus  100  provided for a car  200  as an example of a mobile object, according to the present embodiment. 
     In  FIG. 5 , the distance-measuring apparatus  100  is attached to the inner surface of the windshield of the car  200  at the center. The distance-measuring apparatus  100  includes the LiDAR range finder  110  and the stereo camera unit  120 . Both the LiDAR range finder  110  and the stereo camera unit  120  are disposed such that the distance-measuring ranges of these devices exist ahead of the mobile object. It is assumed that the LiDAR range finder  110  is arranged between the stereo cameras (i.e., two imaging devices) of the stereo camera unit  120  (preferably, in the middle). 
     The LiDAR range finder  110  is referred to as a LiDAR device, and emits pulsed extravisual laser beams using a laser diode (LD). Then, the LiDAR range finder  110  measures the length of time it takes for the pulse to return to calculate the distance. Such a method of calculating the distance is referred to as a time-of-flight (TOF) method. The direction and distance where a pulse of light is reflected at a certain moment are recorded as a point on a three-dimensional map around the LiDAR range finder  110 . 
     Laser Irradiation Field of LiDAR Range Finder 
       FIG. 6A  and  FIG. 6B  are diagrams each illustrating the irradiation field of the laser beams emitted by the LiDAR range finder  110 , according to the present embodiment. 
       FIG. 6A  is a top view of the car  200 , according to the present embodiment. 
       FIG. 6B  is a side view of the car  200 , according to the present embodiment. 
     As illustrated in  FIG. 6A , the LiDAR range finder  110  emits laser beams while scanning a prescribed range ahead of the distance-measuring apparatus in the directions of travel of the car  200  (irradiation field in the side to side directions) in the horizontal direction. Note that the laser beam may be regarded as light or an electromagnetic wave. 
     As illustrated in  FIG. 6B , the LiDAR range finder  110  emits laser beams towards a prescribed range in the directions of travel of the car  200 . How far the laser beams can reach depends on the output power of the LiDAR range finder  110 . Typically, the distance-measurable range is about several hundreds of meters. On the other hand, the distance-measurable range on a close side may be less than one meter. However, typically, the necessity for distance measurement in such a close range is low. For this reason, the distance-detectable range may be set as desired. 
     The LiDAR range finder  110  is configured to perform scanning in the horizontal directions while rotating the irradiation direction of the laser beams in an elevation-angle direction. Due to this configuration, an irradiation field of any distance including a close distance and a long distance can be irradiated with light with reference to the installed position of the LiDAR range finder  110 . 
     Size of Distance-Measuring Apparatus 
     For example, the distance-measuring apparatus  100  that is mounted in a vehicle has a smaller size as much as possible. As a stereo camera needs to capture an image of the scene ahead of the vehicle, the position at which the stereo camera is disposed is limited so as not to interrupt or obstruct the driver&#39;s view ahead of the vehicle. In most cases, a stereo camera is disposed inside the car. In other words, a stereo camera is disposed in the limited space so as not to disturb the occupants of the vehicle. For example, given that a stereo camera is disposed within the front windshield ahead of the rear-view mirror, preferably, the size of the stereo camera is so small that the driver who has to view or manipulate the rear-view mirror is not disturbed by the existence of the stereo camera. 
       FIG. 7  is an external view of the distance-measuring apparatus  100  installed in a vehicle in front of a rear-view mirror  501 , according to the present embodiment. 
     The distance-measuring apparatus  100  is arranged in the center in the vehicle width direction and on the ceiling between the rear-view mirror  501  and the front windshield. Moreover, the LiDAR range finder  110  is disposed as an imaging device between the right camera  11  and left camera  12 . In other words, the right camera  11 , the left camera  12 , and the LiDAR range finder  110  are disposed in a straight line. As described above, according to the present embodiment, the LiDAR range finder  110  and the stereo camera unit  120  are accommodated in a single housing. Due to this configuration, the number of assembling steps can be reduced. 
     Preferably, the width of the distance-measuring apparatus  100  is narrower than the width of the rear-view mirror  501  such that the driver is not disturbed or obstructed by the distance-measuring apparatus  100 . Although the rear-view mirror  501  may have a varying size, preferably, the width of the distance-measuring apparatus  100  is equal to or narrower than, for example, 30 cm when it is assumed that the width of a general-purpose rear-view mirror is 30 cm. 
     At minimum, the width of the distance-measuring apparatus  100  needs to be wider than the width of the LiDAR range finder  110  when the LiDAR range finder  110  is disposed between the right camera  11  and left camera  12 , For this reason, the width of the distance-measuring apparatus  100  may be defined as follows.
 
Width of LiDAR Range Finder  110 &lt;Width of Distance-measuring Apparatus  100 &lt;30 cm
 
     The width of the LiDAR range finder  110  may vary depending on, for example, the design, manufacturing technology, and the required precision, but it is considered that the minimum width of the LiDAR range finder  110  is, for example, at least 4 or 5 cm. For this reason, the width of the distance-measuring apparatus  100  may be defined as follows.
 
4 to 5 cm≤Width of Distance-measuring apparatus  100 ≤30 cm
 
     It is known in the art the distance resolution is low at a remote point when the base-line length of the stereo camera is too short. Note also that the distance resolution depends on the pitches of pixels and the focal length. For example, when it is assumed that the base-line length of a stereo camera with desired capability is 8 cm, the width of the distance-measuring apparatus  100  needs to be equal to or wider than 8 cm. For this reason, the width of the distance-measuring apparatus  100  may be defined as follows.
 
8 cm≤Width of Distance-measuring Apparatus  100 ≤30 cm
 
     As described above, the distance-measuring apparatus  100  according to the present embodiment can be implemented with a significantly smaller size than the sizes in the related art. 
     Hardware Configuration of Distance-measuring Apparatus 
     A schematic configuration of the distance-measuring apparatus  100  according to the present embodiment is described below with reference to  FIG. 8 . 
       FIG. 8  is a diagram illustrating a schematic configuration of the distance-measuring apparatus  100  according to the present embodiment. 
     The distance-measuring apparatus  100  is configured such that the LiDAR range finder  110  and the stereo camera unit  120  can exchange data with each other as desired. As described above, the distance-measuring apparatus  100  is provided with the stereo camera unit  120  that processes a reference image and a comparison image to output a distance image, in addition to the right camera  11  and the left camera  12 . 
     The LiDAR range finder  110  outputs the reflected signals that are obtained in chronological order to the stereo camera unit  120 . Furthermore, the LiDAR range finder  110  may output the distance information of each irradiation direction to the stereo camera unit  120 . Note also that the distance information can be calculated from the reflected signals. 
     The stereo camera unit  120  generates a detailed distance image using a reflected signal obtained for each irradiation direction, and outputs the generated distance image to an electronic control unit (ECU)  190 . As a fusion between the LiDAR range finder  110  and the stereo camera unit  120  is performed as described above, three-dimensional data with a high degree of precision can be obtained. 
     Alternatively, the stereo camera unit  120  may output a processing range that predicts a peak of a reflected signal to the LiDAR range finder  110 . As the stereo camera unit  120  performs block matching to compute the distance to each pixel, the stereo camera unit  120  can estimate the distance to an object existing in an irradiation field. When it is assumed that the neighborhood of the estimated distance is the processing range, there is high possibility that a peak of a reflected signal is within a processing range, and the LiDAR range finder  110  detects a peak of the reflected signal from the processing range. Due to this configuration, a peak can be detected even when a peak is buried in noise. 
     In  FIG. 8 , by way of example, the distance images and the reference images are sent out to an electronic control unit (ECU)  190 . The ECU  190  is an electronic control unit provided for a vehicle. The distance-measuring apparatus  100  that is mounted in a vehicle may be referred to as an on-vehicle device in the following description. The ECU  190  performs various kinds of driver assistance using the distance images and reference images output from the distance-measuring apparatus  100 . Various kinds of pattern matching is performed on a reference image to recognize the conditions of, for example, a preceding vehicle, pedestrian, white line, and a traffic signal. 
     There are varying kinds of driver assistance depending on the type of vehicle. For example, when the side-to-side positions of an object overlaps with the vehicle width of the user&#39;s vehicle, warning or braking is performed as driver assistance depending on the time to collision (TTC) calculated from the distance and the relative velocity. When it is difficult to stop the vehicle before a collision occurs, the steering is controlled so as to avoid a collision. 
     Moreover, the ECU  190  performs adaptive cruise control (ACC) to follow the preceding vehicle with a following distance that varies depending on the vehicle speed. Once a preceding vehicle stops, the user&#39;s vehicle is also stopped. When the preceding vehicle starts moving, the user&#39;s vehicle is also starts moving. For example, when the ECU  190  is capable of recognizing a white line, lane keeping assist may be performed to control the steering such that the user&#39;s vehicle travels forward in the center of the traffic lane. Moreover, when there is some concern that the user&#39;s vehicle departs from the traffic lane, for example, lane-departure prevention may be performed to shift the direction of travel towards the traffic lane. 
     When an obstacle is detected in the directions of travel when the user&#39;s vehicle is stopped, unintended acceleration can be prevented. For example, when an obstacle is detected in the directions of travel that are determined by the operative position of a shift lever and the amount of force applied to the accelerator pedal is large, a possible damage can be reduced by warning or ceasing the engine output. 
       FIG. 9  is a diagram illustrating a hardware configuration of the distance-measuring apparatus  100  according to the present embodiment. 
     The distance-measuring apparatus  100  includes a sensor stay  201  and a control board housing  202 . Among those elements, only the control board housing  202  that performs computation may be referred to as the distance-measuring apparatus  100 . In such a configuration, a system that includes the control board housing  202  and the sensor stay  201  that includes a plurality of cameras and an irradiation unit that emits laser beams and a light receiver that receives laser beams is referred to as a distance-measuring system. 
     The left camera  12 , the right camera  11 , and the LiDAR range finder  110  are mounted into the sensor stay  201 . As the LiDAR range finder  110  is disposed on the straight lines positioned between the right camera  11  and the left camera  12 , the distance-measuring apparatus  100  can be downsized and produced at low cost. The spacing between the right camera  11  and the left camera  12  is referred to as the base-line length. When the base-line length is longer, the distance resolution at a remote point can be improved more easily. The base-line length needs to be shortened in order to downsize the distance-measuring apparatus  100 . Preferably, the base-line length is shortened but high degree of precision is maintained. 
     The control board housing  202  accommodates a laser signal processor  240 , a stereo image computation unit  250 , a memory  260 , and a micro processing unit (MPU)  270 . As the laser signal processor  240  is separately arranged from the LiDAR range finder  110 , the size of the LiDAR range finder  110  can be reduced. Due to this configuration, the LiDAR range finder  110  can be disposed between the right camera  11  and left camera  12  in the present embodiment. 
     In  FIG. 9 , the stereo image computation unit  250  and the laser signal processor  240  are configured by separate circuit boards. However, no limitation is indicated thereby, and the stereo image computation unit  250  and the laser signal processor  240  may be configured a circuit board in common. By so doing, the number of circuit boards is reduced, and the production cost can be reduced. 
     The elements on the sensor stay  201  side are described below in detail. As illustrated in  FIG. 9 , the left camera  12  includes a camera lens  211 , a imaging device  212 , and a sensor substrate  213 . The extraneous light that has passed through the camera lens  211  is received by the imaging device  212 , and is photoelectrically converted in a predetermined frame cycle. The signals that are obtained as a result of the above photoelectric conversion are processed by the sensor substrate  213 , and a captured image is generated for each frame. The generated captured image is sequentially sent to the stereo image computation unit  250  as a comparison image. 
     The right camera  11  has a configuration similar to that of the left camera  12 , and captures an image based on a synchronous control signal in synchronization with the left camera  12 . The captured image is sequentially sent to the stereo image computation unit  250  as a reference image. 
     The LiDAR range finder  110  includes a light source driver  231 , a laser beam source  232 , and a projector lens  233 . The light source driver  231  operates based on a synchronous control signal sent from the laser signal processor  240 , and applies modulating electric current (light-source driving signal) to the laser beam source  232 . Due to this configuration, the laser beam source  232  emits laser beams. The laser beams that are emitted from the laser beam source  232  are emitted to the outside through the projector lens  233 . 
     In the present embodiment, it is assumed that an infrared semiconductor laser diode (LD) is used as the laser beam source  232 , and near-infrared light with wavelengths of 800 nanometer (nm) to 950 nm is emitted as a laser beam. Moreover, it is assumed that the laser beam source  232  emits a laser beam having a pulsed waveform at prescribed time intervals according to the modulating electric current (light-source driving signal) applied by the light source driver  231 . Further, it is assumed that the laser beam source  232  emits a pulsed laser beam having a short pulse width of about a few nanoseconds to several hundreds of nanoseconds at prescribed time intervals. However, no limitation is intended thereby, and the wavelengths of the laser beams or the pulse widths may be set differently. In some embodiment, other types of light emitting elements such as vertical-cavity surface-emitting lasers (VCSELs), organic electroluminescence (EL) elements, and LEDs may be used as a light source. 
     The pulsed laser beams that are emitted from the laser beam source  232  are emitted to the outside through the projector lens  233 , and then an object existing in the irradiation direction of one of the laser beams is irradiated with some of the laser beams emitted through the projector lens  233 . Note also that the laser beams that are emitted from the laser beam source  232  are approximately collimated by the projector lens  233 . Accordingly, the irradiation area of the object is controlled to a predetermined minute area. 
     The LiDAR range finder  110  further includes a light-receptive lens  234 , a light-receiving element  235 , and a light-signal amplifier circuit  236 . The laser beams that are emitted to the object existing in the irradiation direction of one of the laser beams uniformly scatter to all directions. Then, only the light components that are reflected and return in the same optical path as the laser beams that were emitted from the LiDAR range finder  110  are guided to the light-receiving element  235  through the light-receptive lens  234  as reflected light. 
     In the present embodiment, a silicon pin photodiode or an avalanche photodiode is used as the light-receiving element  235 . The light-receiving element  235  photoelectrically converts the reflected light to generate a reflected signal, and the light-signal amplifier circuit  236  amplifies the generated reflected signal and then sends the amplified reflected signal to the laser signal processor  240 . The reflected signal may be converted into a digital signal before output to the laser signal processor  240 , or may be converted into a digital signal by the laser signal processor  240 . 
     The elements on the control board housing  202  side are described below in detail. The laser signal processor  240  sends the reflected signal sent from the LiDAR range finder  110  and the distance data that is calculated based on the reflected signal to the stereo image computation unit  250 . The laser signal processor  240  may detect a peak from the reflected signal to calculate and obtain the distance information. In the present embodiment, any one of the stereo image computation unit  250  and the laser signal processor  240  may calculate the distance information. 
     The stereo image computation unit  250  is configured by, for example, a dedicated integrated circuit such as a field programmable gate array (FPGA) and an application specific integrated circuit (ASIC). The stereo image computation unit  250  outputs a synchronous control signal for controlling the timing of capturing an image and the timing of laser-beam projection and laser-beam reception to the left camera  12 , the right camera  11 , and the laser signal processor  240 . 
     The stereo image computation unit  250  generates a distance image based on a comparison image sent from the left camera  12 , a reference image sent from the right camera  11 , and a reflected signal sent from the laser signal processor  240 . The stereo image computation unit  250  stores the generated distance image in the memory  260 . 
     The memory  260  stores a distance image and a reference image generated by the stereo image computation unit  250 . The memory  260  serves as a work area where the stereo image computation unit  250  and the MPU  270  performs various kinds of processes. 
     The MPU  270  controls the elements accommodated in the control board housing  202 , and analyzes a disparity image stored in the memory  260 . Moreover, the MPU  270  sends the distance image and the reference image to the ECU  190 . 
     Problems in TOF Distance-measuring Method 
     In the TOF distance-measuring method implemented by the laser signal processor  240 , signals are received as in a first equation given below. 
     
       
         
           
             
               
                 
                   
                     
                       P 
                       r 
                     
                     = 
                     
                       
                         A 
                         
                           L 
                           2 
                         
                       
                       · 
                       
                         R 
                         Tgt 
                       
                     
                   
                   ⁣ 
                   
                     · 
                     
                       P 
                       0 
                     
                   
                 
               
               
                 
                   First 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   Equation 
                 
               
             
           
         
       
     
     P r : Amount of Received Reflected Signal 
     L: Detection Distance to Object 
     R Tgt : Reflectance Ratio of Object 
     P O : Intensity of Light Emission from Light Emitter 
     A: Constant determined by Optical System or Mechanical System 
     The distance can be measured based on the length of time between a point in time when a laser beam is emitted and a point in time when the laser beam is received after being reflected by an object. As understood from the first equation, the strength of the signal Pr received by the LiDAR range finder  110  is influenced by the square of the distance. For example, when it is assumed that the reflectance ratio R Tgt  or S snd  of a target object is the same and the distance L is doubled (for example, when the distance is doubled from 10 m to 20 m), the signal level is reduced to a quarter. 
     For example, Po may be enhanced, TFG may be improved, or Srcv may be increased in order to earn the distance range. However, when Po is enhanced, saturation may occur at a short-distance portion as the signal gets too strong. If such saturation occur, a peak may be lost and an error may occur, and the cost may also increase. When Srcv is increased, the size of a module may also increase. Even when TFG is improved, a dramatic improvement cannot be expected. 
       FIG. 10A  and  FIG. 10B  are diagrams illustrating an example of a difference in signal level between a signal level received at a close point and a signal level received at a remote point. 
       FIG. 10A  illustrates reflected signals obtained as light is reflected by close objects. 
     Each of the reflected signals indicates a peak of a signal Pr, and the rest of the signal Pr is noise. As illustrated in  FIG. 10A , the signal levels of close objects are strong, and signals can be distinguished from noise when detected. The distance to an object is calculated based on the length of time taken until a reflected signal is detected. There are various kinds of methods to determine the level of a reflected signal based on the signal Pr. For example, the highest peak may be detected or a plurality of points equal to or higher than a threshold may be detected (multiple detection). Typically, a method in which a reflected signal is binarized with a threshold is adopted. By contrast, in the present embodiment, the reflected signal as illustrated in  FIG. 10A  is output to the stereo image computation unit as it is, or the reflected signal on which filtering or the like has been done is output to the stereo image computation unit. The stereo image computation unit converts the reflected signal into a cost, and performs a fusion between the obtained cost and the cost of block matching. Note also that the block matching may be simple matching instead of matching on a block-by-block basis. For example, matching may be performed on a pixel-by-pixel basis. 
       FIG. 10B  illustrates a reflected signal obtained as light is reflected by a remote object. When the signal level of such a remote object is weak and the strength of its reflected signal is almost the same as that of noise, it is difficult to detect the reflected signal with any desired one of a method in which the highest peak is detected and a method in which a signal level equal to or higher than a threshold is detected. 
     Typically, a signal Pr whose level of signal is equal to or greater than a threshold is detected as a reflected signal in ascending distance order, or a peak position is detected. However, as illustrated in  FIG. 10B , the substantial strength of a reflected signal is equivalent to the strength of noise that is detected in advance. Accordingly, when signal levels are viewed in its entirety, it is difficult to detect a reflected signal. Theoretically, the LiDAR range finder  110  has such a drawback as above. However, a principle fusion is adopted in the present embodiment, and thus the distance to an object at a long distance may be detected with practical precision as long as the peak is higher is slightly higher than the levels of noise. 
     Laser-beam Resolution of Laser Beams according to Present Embodiment 
     For example, the distance-measuring apparatus  100  according to the present embodiment is characterized by emitting a laser beam of low laser-beam resolution. Emission of a laser beam of low laser-beam resolution is described below with reference to  FIG. 11A ,  FIG. 11B ,  FIG. 12A ,  FIG. 12B , and  FIG. 12C . 
       FIG. 11A  and  FIG. 11B  are diagrams each illustrating a scene in which a laser beam is emitted, according to the present embodiment. 
       FIG. 11A  is a diagram illustrating a scene in which a laser beam is emitted, according to the present embodiment. 
       FIG. 11B  is a magnified view of  FIG. 11A . 
     As described above, according to the present embodiment, the distance-measuring apparatus  100  irradiates an area including at least one object with a laser beam of low laser-beam resolution, and performs image processing using a reflected signal with multiple pulses to separate two or more objects that exist within a laser-beam resolution from each other with an appropriate plane that indicates the distance. In other words, the laser-beam resolution of the LiDAR is not necessarily high and may be low. 
       FIG. 12A ,  FIG. 12B , and  FIG. 12C  are diagrams each illustrating an image of irradiation when a laser beam of low laser-beam resolution is emitted, according to the present embodiment. 
     In  FIG. 12A , each vertically-oriented rectangle indicates an irradiation field  101  of one laser beam. 
     In  FIG. 12B , each horizontally-oriented rectangle indicates the irradiation field  101  of one laser beam. 
     In  FIG. 12C , each roughly-drawn square indicates the irradiation field  101  of one laser beam. 
     As an object at a remote point is captured at an upper point of an image, a plurality of objects at varying distances tend to be included in one irradiation field  101  when the irradiation field is vertically oriented. Accordingly, a distance appears between two peaks in multiple pulses, and those peaks can easily be separated from each other. As a plurality of peaks can be detected, the planes each of which indicates the distance of a plurality of objects included in one irradiation field  101  can easily be separated from each other. 
     By contrast, when the irradiation field is horizontally oriented, there is little likelihood that a plurality of object at varying distances are included in one irradiation field  101 , and it is expected that the number of peaks in one reflected signal will be reduced. As will be described later in detail, the peaks of a reflected signal are used in the principle fusion. For this reason, the processing load on the fusion operation can be lightened. 
     As described above, the glancing angle of a laser beam may be horizontally oriented or vertically oriented according to the present embodiment. Moreover, a horizontally-oriented irradiation field  101  and a vertically-oriented irradiation field  101  may exist in a mixed manner. Further, even if a reflected signal is extremely weak, it is expected that the magnitudes of peaks of the multiple pulses of the reflected signal (voltage value) can be separated from each other by surface on an object-by-object basis as long as each peak is slightly higher than the levels of noise. 
     A low laser-beam resolution is defined as below. A low laser-beam resolution refers to a laser beam whose at least one of the resolution in the vertical direction and the resolution in the horizontal direction exceeds two degrees. By emitting a laser beam of low laser-beam resolution, an image can be separated by surface at an appropriate distance. Regarding the laser-beam resolution according to the related art, for example, the resolution in the horizontal direction is about 0.1 to 0.4 degrees, and the resolution in the vertical direction is about 2 degrees. In other words, the laser-beam resolution in the distance-measuring apparatus  100  according to the present embodiment may be lower than the laser-beam resolution in the related art. 
       FIG. 13A  and  FIG. 13B  are diagrams each illustrating a configuration of the irradiation unit of the LiDAR range finder  110  in which a low laser-beam resolution as illustrated in  FIG. 12A ,  FIG. 12B , and  FIG. 12C  is implemented, according to the present embodiment. 
     As illustrated in  FIG. 13A , the LiDAR range finder  110  has a scanning mirror  237  that deflects and scans the light emitted from the laser beam source  232  so as to be reflected towards an effective scanning area. For example, a micro-electromechanical system (MEMS) mirror in which the mirror unit is driven by MEMS may be used as the scanning mirror  237 , and a polygon mirror that is rotated by a motor or other kinds of galvano mirror may be used as the scanning mirror  237 . 
     The laser beams that are emitted from the laser beam source  232  pass through the projector lens  233  and reach the scanning mirror  237 . The projector lens  233  is a coupling lens or a collimator lens, and performs optical adjustment so that the light beam is collimated. Typically, the distance between the laser beam source  232  and the projector lens  233  matches the focal length of the projector lens  233 . By contrast, in the present embodiment, the distance between the laser beam source  232  and the projector lens  233  is made slightly longer than the focal length of the projector lens  233  in order to achieve a low laser-beam resolution. The degree of extension may experimentally be determined. In addition to a configuration where the focal length is adjusted, the projector lens  233  may be a concave lens that spreads a laser beam. 
     The port of the laser beam source  232  from which laser beams are emitted may be covered with a mask that has a vertically-oriented or horizontally-oriented slot to make the shape of the irradiation field vertically oriented or horizontally oriented. Alternatively, as illustrated in  FIG. 13B , a plurality of laser diodes (LDs)  238  each of which is a point source of light may be arranged in a desired shape of irradiation field (vertically oriented, horizontally oriented, or square-shaped). In  FIG. 13B , the multiple LDs  238  are horizontally oriented. Alternatively, the multiple LDs  238  may have a irradiation field of any desired shape such as a triangle or a circle. 
     Alternatively, for example, a method in which a coupling lens with different focal lengths in the vertical direction and the horizontal direction is used or a method in which various kinds of multiple lens are combined may be adopted. 
     Functional Configuration of Stereo Image Computation Unit 
       FIG. 14  is a block diagram illustrating the functions of the distance-measuring apparatus  100  according to the present embodiment. 
     In particular,  FIG. 14  illustrates the functions of the stereo image computation unit  250  according to the present embodiment. As illustrated in  FIG. 14 , the stereo image computation unit  250  includes a distortion corrector  13  to which the reference images and comparison images obtained by the right camera  11  and the left camera  12 , which together make up a stereo camera, are input, and a distance computing unit  14  that performs principle fusion. In the present embodiment, the images captured by the right camera  11  are used as reference images, and the images captured by the left camera  12  are used as comparison images. 
     The distortion corrector  13  and the distance computing unit  14  may be implemented by a dedicated electronic circuit, or a program that implements each element may be implemented as executed by a central processing unit (computer). In such cases, the stereo image computation unit  250  may serve as an information processing device. The stereo image computation unit  250  may serve as an image processing device that performs image processing. 
     The distortion corrector  13  performs general-purpose distortion correction on the reference images and comparison images. Due to this image correction, the reference images and the comparison images are corrected to eliminate all the differences just except disparities. The image correction is implemented by calibration that is performed in advance. For example, the left camera  12  and the right camera  11  capture an object for correction (for example, a chart in a checkerboard pattern) at the time of installation. A pair of images are compared with each other to generate a look up table (LUT) for geometric transformation in which the image data is converted so as to minimize an internal error factor in hardware such as the distortion in a lens of a camera, displacements in optical axis, displacements in focal length, and the distortion in an imaging device. The distortion corrector  13  performs image correction with reference to such a LUT. 
     The distance computing unit  14  calculates a disparity by applying algorithms such as block matching or semi-global matching (SGM) propagation to the reference images and comparison images. As will be described later in detail, the distance computing unit  14  performs a principle fusion where fusion is performed between the data obtained by the stereo camera unit  120  and the data obtained by the LiDAR range finder  110  at an early stage. 
     In order to achieve such functions, the distance computing unit  14  includes a data acquisition unit  21 , a stereo matching unit  23 , a semi-global matching (SGM) unit  24 , a distance interpolator  25 , a reflected-signal cost converter  26 , a determination unit  27 , a distance calculator  28 , a fusion unit  29 , a distance-image generation unit  30 , and a pixel-range determination unit  31 . 
     The data acquisition unit  21  obtains the irradiation direction, the distance information, and a reflected signal from the laser signal processor  240 , for each one of the emitted laser beams. The reflected signal may be an analog signal or a digital signal. The distance data is not necessarily obtained. 
     The stereo matching unit  23  performs block matching on the reference images and the comparison images to calculate a disparity (obtain a disparity as a result of conversion). The SGM unit  24  performs the SGM (semi-global matching (SGM) propagation) to calculate a disparity. The distance interpolator  25  converts the cost of disparity space into a cost of metric space (Z-space), and further interpolates the distance at regular intervals. 
     The reflected-signal cost converter  26  converts a reflected signal into a LiDAR cost C LI (p, Z). 
     The fusion unit  29  performs a principle fusion. In other words, the fusion unit  29  performs a fusion between the stereo-matching cost C ST  and the LiDAR cost C LI , or performs a fusion between the synthesis cost Ls(p, d) and the LiDAR C LI (p, Z). As another way of performing a fusion, the fusion unit  29  performs a principle fusion to replace the distance that each pixel of an irradiation field has with the distance information that is obtained from the peak of the reflected signal output from the laser signal processor  240 . 
     The distance calculator  28  detects a peak from the reflected signal to calculate the distance at which the peak is detected based on the reflected signal. In other words, the distance calculator  28  of the stereo image computation unit  250  can calculate the distance information based on a threshold or the like that is different from the values used on the laser signal processor  240  side. However, the distance information that is sent from the laser signal processor  240  may be used just as it is for processing. In such a configuration, the distance calculator  28  may be omitted. 
     The pixel-range determination unit  31  refers to an irradiation-direction pixel-range table  32 , and determines a pixel range for each one of the laser beams based on the irradiation direction. 
     The determination unit  27  performs some determinations as follows. 
     (i) Whether there is a distance equivalent to the distance information calculated and obtained by the distance calculator  28  in a pixel range is determined. When there is a distance equivalent to the distance information calculated and obtained by the distance calculator  28  in a pixel range, the corresponding pixel is determined. 
     (ii) Whether a reflected signal has a peak and the peak corresponds to the distance information that is equivalent to the distance of a pixel obtained by performing block matching is determined. 
     As will be described later in detail, these determinations as in (i) and (ii) are used for the principle fusion according to the present embodiment. 
     The distance-image generation unit  30  generate a distance image where the distance to each one of the pixels obtained in the principle fusion is associated with corresponding one of the pixels of a reference image. 
     The configuration as illustrated in  FIG. 14  is given by way of example, and no limitation is indicated thereby. For example, the laser signal processor  240  and the stereo image computation unit  250  may be combined together. Alternatively, the laser signal processor  240  may have some of the functions of the stereo image computation unit  250 . Alternatively, the ECU  190  may have some of or the entirety of the functions of the stereo image computation unit  250 . 
     Principle of Distance Measurement by Stereo Camera 
     The functions of the stereo matching unit  23 , the SGM unit  24 , the distance interpolator  25 , the reflected-signal cost converter  26 , the distance calculator  28 , the fusion unit  29 , and the pixel-range determination unit  31  of the distance computing unit  14  are described below in detail. 
     Stereo Matching Unit 
       FIG. 15A  is a diagram in which a base pixel is indicated on a base image. 
       FIG. 15B  is a diagram in which an amount of shift (i.e., amount of displacement) is calculated while sequentially shifting a candidate pixel on a comparison image that corresponds to the base pixel of  FIG. 15A . 
       FIG. 16  is a graph in which the cost value is indicated for each degree of the amount of shift, according to the present embodiment. 
     In the present embodiment, the corresponding pixel indicates a pixel of a comparison image that is most similar to the base pixel of a base image. 
     As illustrated in  FIG. 15A  and  FIG. 15B , the cost C(p, d) of each candidate pixel q(x+d, y) that corresponds to the base pixel p(x, y) is calculated based on the multiple brightness values of a specific base pixel p(x, y) in a reference image and a plurality of candidate pixels q(x+d, y), which corresponds to the base pixel p(x, y), on an epipolar line drawn on a comparison image. “d” in  FIG. 15B  indicates the amount of shift (i.e. amount of displacement) of the candidate pixel q that corresponds to the base pixel p. In the present example embodiment, the amount of shift is indicated on a pixel-by-pixel basis. In other words, the stereo-matching cost C ST  (p, d) that indicate the degree of dissimilarity in brightness value between the candidate pixels q(x+d, y) and the base pixel p(x, y) are calculated while sequentially shifting the candidate pixels q(x+d, y) on a pixel-by-pixel basis within a prescribed range (for example, 0&lt;d&lt;25), as illustrated in  FIG. 15A  and  FIG. 15B . A known method such as the sum of absolute difference (SAD) may be applied to a method of calculating of the stereo-matching cost C ST . In this configuration, the stereo-matching cost C ST  indicates the degree of dissimilarity. 
     As illustrated in  FIG. 16 , the stereo-matching cost C ST (p, d) as calculated as above can be depicted in a graph of cost curve where a collection of the stereo-matching costs C ST  are indicated for each degree of amount of shift “d.” As illustrated in  FIG. 16 , the stereo-matching cost C ST  becomes 0 (zero) when the amount of shift “d” is 5, 12, and 19, and thus a minimum value cannot be calculated. As described above, it is difficult to obtain a minimum value for the stereo-matching cost C ST  when an object with a little texture is observed. 
     SGM Unit 
     A distance-measuring method in which SGM is used is described below with reference to  FIG. 17  and  FIG. 18 . The SGM is adopted to precisely derive the disparity value even from an object with a little texture. In the SGM, a high-density disparity image is derived based on a reference image. As the detailed information of a road or the like with a little texture can be expressed in the SGM, more precise distance measuring is achieved. 
     In the SGM, a disparity value is not calculated immediately after a cost value that indicates the degree of dissimilarity is calculated. Instead, a synthesis-cost value that indicates the degree of dissimilarity in synthesis is further calculated to derive a disparity value after the cost value is calculated. By so doing, a disparity image (high-density disparity image) in which the disparity values are obtained for almost all the pixels is finally derived. 
       FIG. 17  is a schematic view of how a synthesis cost is derived according to the present embodiment. 
       FIG. 18  is a graph of synthesis-cost curve indicating the synthesis cost for each one of the disparity values, according to the present embodiment. 
     In addition to the calculation of the stereo-matching cost C ST (p, d), in the method of calculating a synthesis-cost according to the present embodiment, the cost values calculated for a plurality of base pixels around the prescribed base pixel p(x, y) are aggregated with the stereo-matching cost C ST (p, d) to calculate a synthesis-cost value Ls(p, d). 
     More detailed explanation about a method of calculating a synthesis-cost value is given below. Firstly, path cost values Lr(p, d) need to be calculated prior to calculating a synthesis-cost value Ls(p, d). The path cost values Lr(p, d) are calculated as in the second equation given below, and the synthesis cost Ls is calculated as in the third equation given below. 
     Second Equation
 
 Lr ( p,d )= C ( p,d )+min{( Lr ( p−r,d ), Lr ( p−r,d− 1)+ P 1, Lr ( p−r,d+ 1)+ P 1, Lr min( p - R )+ p 2}
 
     In the second equation, “r” indicates a directional vector of aggregation, and includes the two components of X-direction and Y-direction. “min{ }” is a function to calculate a minimum value. “Lmin(p−r)” indicates the minimum value of Lr(p−r, d) when the amount of shift “d” is varied in the coordinates where “p” is shifted to “r” by one pixel. As indicated in the second equation, “Lr” is recursively used. “P1” and “P2” are fixed parameters that are determined in advance by experiment. “P1” and “P2” are designed such that the disparity values Δ of the neighboring base pixels in the path become consecutive. For example, P1=48 and P2=96. 
     As illustrated in the second equation, Lr(p, d) are calculated by adding minimum values for the path cost values Lr of pixels in r directions illustrated in  FIG. 17  to the cost value C for the base pixel p(x, y). As Lr are calculated for a plurality of pixels in r-directions as described above, Lr for the end pixels in the r-directions of the base pixel p(x, y) are firstly calculated and then Lr for the other pixels are calculated in the r-directions. 
     Then, as illustrated in  FIG. 17 , Lr0, Lr45, Lr90, Lr135, Lr180, Lr225, Lr270, and Lr315 in eight directions are obtained, and a synthesis-cost value Ls is finally calculated as in the third equation. 
     
       
         
           
             
               
                 
                   
                     
                       L 
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                         p 
                         , 
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                         ( 
                         
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     As illustrated in  FIG. 18 , the synthesis-cost values Ls(p, d) as calculated above can be depicted in a graph of synthesis-cost curve where the synthesis-cost values Ls(p, d) are indicated for each degree of amount of shift “d.” As illustrated in  FIG. 18 , the synthesis-cost value Ls has the minimum value when the amount of shift “d” is 3. Accordingly, it can be calculated as a disparity value Δ=3. 
     In the example embodiment as described above, the number of paths “r” is eight. However, no limitation is intended thereby. For example, the eight directions may be further divided by two or three into sixteen directions or twenty-four directions, respectively. 
     In the example embodiment as described above, the cost C is indicated as the “degree of dissimilarity.” However, no limitation is indicated thereby, and the cost C may be indicated as the “degree of similarity” as the reciprocal of dissimilarity. In such cases, a known method such as the normalized cross-correlation (NCC) is applied to the method of calculating the cost C, and the disparity value A where the synthesis cost Ls becomes maximum is obtained and the disparity value A where the synthesis cost Ls becomes minimum is not obtained. Alternatively, the cost C may be indicated as the “degree of match” that includes both the degree of dissimilarity and the degree of similarity. 
     Note also that the semi-global matching (SGM) may be performed before performing a fusion, or may be performed after the fusion is performed. Alternatively, the SGM may be not at all performed. 
     Distance Interpolator 
     The distance interpolator  25  converts the disparity space into Z-space (metric space) in order to perform a fusion between the synthesis cost Ls(p, d) and the reflected signal detected by the LiDAR range finder  110 . 
       FIG. 19  is a diagram illustrating the synthesis cost Ls(p, Z) obtained by converting the synthesis cost Ls(p, d), according to the present embodiment. 
     In  FIG. 19 , the cost of disparity space that is obtained by the SGM is converted into the synthesis cost Ls(p, Z) in the Z-space. As understood from an equation indicating the relation between a disparity d and a distance Z (Z=BF/d), synthesis costs Ls(p, Z) can not be obtained at equal intervals in the Z space. 
     In order to handle such a situation, the fusion unit  29  interpolates the cost obtained by block matching at regular intervals. In  FIG. 19 , each of the circles indicates the cost obtained by block matching, and each of the rectangles indicates the cost obtained by interpolation. The interpolation method is satisfactory as long as it is suitable for curve fitting, and for example, the parabolic fitting, a high-degree polynomial, and a spline curve can be applied to the interpolation method. In  FIG. 19 , the synthesis cost Ls(p, Z) is calculated by interpolation, for example, for every three meters. 
     In the above example embodiment, interpolation is performed for every three meters. However, no limitation is indicated thereby. One example way of determining the interval is to make the interval be equivalent to the distance resolution of the LiDAR device. 
     Reflected-signal Cost Converter 
       FIG. 20A ,  FIG. 20B , and  FIG. 20C  are diagrams illustrating a method of calculating a LiDAR cost C LI (p, Z) according to the present embodiment. 
       FIG. 20A  is a diagram schematically illustrating the timing at which a pulse of the laser beam  310  is emitted, according to the present embodiment. 
       FIG. 20B  is a diagram illustrating the reflected signals  311  that are sampled in chronological order, according to the present embodiment. 
       FIG. 20C  is a diagram illustrating the LiDAR costs C LI (p, Z) according to the present embodiment. 
     Once the laser beam  310  is emitted, the LiDAR range finder  110  starts sampling the reflected signals  311  at regular time intervals. 
     The duration in time in which the LiDAR range finder  110  continues performing the sampling in response to one-time emission of the laser beam  310  is determined in advance. For example, such duration in time corresponds to the distance of about 100 to 200 m. 
     The relation between the reflected signals  311  and the duration in time as illustrated in  FIG. 20B  indicates that the probability that an object exists at that distance is higher as the value of the reflected signal  311  is greater. On the other hand, the LiDAR cost C LI (p, Z) is minimized at the distance where the probability that at least one object exists is the highest. For this reason, when a fusion is to be performed, preferably, the waveform of the reflected signal  311  is changed in such a manner that the probability that at least one object exists increases as the value of the reflected signal  311  is smaller. Under these circumstances, the reflected-signal cost converter  26  converts the reflected signals  311  as illustrated in  FIG. 20B  into the LiDAR cost C LI (p, Z) as illustrated in  FIG. 20C . Although there are various kinds of methods to perform conversion, it is satisfactory when the LiDAR cost C LI (p, Z) is minimized at the distance where the reflected signal  311  takes the greatest value. For the sake of simplification, for example, conversion may be performed to invert the magnitude of the reflected signal  311  around a certain value of the reflected signal  311 . 
     Alternatively, the values of the reflected signal  311  may be converted using a function that decreases the values of the reflected signal  311  as the value of the reflected signal  311  is greater. 
     In  FIG. 20A ,  FIG. 20B , and  FIG. 20C , the waveform of the reflected signal  311  is converted in such a manner that the probability that at least one object exists increases as the value of the reflected signal  311  is smaller. However, the stereo image computation unit  250  may modify the waveform of the synthesis cost Ls or the stereo-matching costs C ST  so as to be maximized at the distance where the probability that at least one object exists is the highest. 
     Pixel-range Determination Unit 
     In  FIG. 12A ,  FIG. 12B , and  FIG. 12C , the irradiation field of one laser beam is illustrated, and each irradiation field corresponds to a plurality of pixel ranges. Assuming that the irradiation field of each laser beam is fixed (in other words, each laser beam is emitted in almost the same direction even when a reference image is switched), the pixel range can be determined when the irradiation direction is determined. As it can be assumed that the irradiation direction of each laser beam on one reference image is almost the same even when a reference image is switched, each one of the irradiation directions can be associated with a pixel range in advance. 
     
       
         
           
               
            
               
                   
               
               
                 First Table 
               
            
           
           
               
               
               
            
               
                   
                 IRRADIATION DIRECTION 
                 PIXEL RANGE 
               
               
                   
               
               
                   
                 ϕ1, λ1 
                 (Xs1, Ys1) (Xe1, Ye1) 
               
               
                   
                 ϕ2, λ2 
                 (Xs2, Ys2) (Xe2, Ye2) 
               
               
                   
                 ϕ3, λ3 
                 (Xs3, Ys3) (Xe3, Ye3) 
               
               
                   
                 . 
                 . 
               
               
                   
                 . 
                 . 
               
               
                   
                 . 
                 . 
               
               
                   
               
            
           
         
       
     
     The irradiation-direction pixel-range table  32  is described below with reference to a first table given above. The first table illustrates an example of the irradiation-direction pixel-range table  32 . In the irradiation-direction pixel-range table  32 , the irradiation directions and the pixel ranges are associated with each other. ϕ and λ in the irradiation direction indicate the glancing angle in the direction of latitude and the glancing angle in the direction of longitude, respectively. (Xs, Ys) and (Xe, Ye) in the column of pixel range indicate the coordinates of the vertices of a reference image at the opposite angle. 
     By referring to the irradiation-direction pixel-range table  32 , the pixel-range determination unit  31  can determine the pixel range based on the irradiation direction obtained from the LiDAR range finder  110 . 
     Rather than determining the relation between the irradiation direction and the pixel range in advance as in the first table, the pixel-range determination unit  31  may calculate the pixel range based on the irradiation direction. As the pixel that the laser beam that is emitted in a particular irradiation direction hits can be specified based on the irradiation direction, the pixel range can be calculated and obtained by adding a margin depending on the shape of an irradiation field to the specified pixel on the top and bottom sides and the right and left sides. 
     Distance Calculator 
       FIG. 21  is a diagram illustrating the distance information calculated and obtained by the distance calculator  28 , according to the present embodiment. 
     The distance calculator  28  determines a length of time T where the reflected signal takes a value equal to or greater than a threshold Tth, and calculates the distance based on the determined length of time T. For example, as illustrated in  FIG. 21 , when a reflected signal whose voltage value is equal to or greater than the threshold Tth is detected at three distances, three distances La, Lb, and Lc are calculated based on the speed of light and the length of time T it takes from a point in time when a laser beam is emitted until a point in time when a peak is observed (see  FIG. 20A ,  FIG. 20B , and  FIG. 20C ). 
     Distance to Object=Speed of Light×T/2 
     As described above, the distance calculator  28  can convert the length of time T into distance information. 
     Alternatively, the distances of high-order N peaks in descending order of the value may be calculated without using any threshold. Due to such a configuration, an object at a long distance can be detected. 
     Fusion Unit 
     Typically, the fusion unit  29  adopts one of the two methods given below to perform a fusion (principle fusion) between the data obtained by the LiDAR range finder  110  and the data obtained by a stereo camera. In one of the two methods, a fusion is performed based on the cost. In the other one of the two methods, the distance to each pixel obtained by performing block matching is replaced with the distance information detected by the LiDAR range finder  110 . Each of these two methods is an example of the principle fusion according to the present embodiment. 
     Fusion based on Cost 
     Firstly, how a fusion is performed based on a cost is described below. The fusion unit  29  performs a fusion between the synthesis cost Ls(p, Z) and the LiDAR cost C LI (p, Z) to calculate a cost C(p, Z). Alternatively, the fusion unit  29  can perform a fusion between the stereo-matching cost C ST (p, Z) and the LiDAR cost C LI (p, Z) before the semi-global matching (SGM) is performed. 
       FIG. 22A ,  FIG. 22B , and  FIG. 22C  are schematic diagrams of a fusion between synthesis costs Ls(p, Z) and LiDAR costs C LI (p, Z), according to the present embodiment. 
       FIG. 22A  illustrates the LiDAR costs C LI (p, Z) according to the present embodiment. 
       FIG. 22B  illustrates the synthesis costs Ls(p, Z) according to the present embodiment. 
     Firstly, the fusion unit  29  multiplies each one of the LiDAR costs C LI (p, Z) by a coefficient A, and multiplies each one of the synthesis costs Ls(p, Z) by a coefficient B. Then, the fusion unit  29  adds up each pair of the obtained values at the same distance. Due to the interpolation performed for the synthesis costs Ls(p, Z) as described above, the costs are obtained at almost the same distances between the synthesis costs Ls(p, Z) and the LiDAR costs C LI (p, Z). When necessary, interpolation may also be performed for the LiDAR costs C LI (p, Z) in a similar manner. 
     Due to this configuration, as illustrated in  FIG. 22C , a fusion can be performed between the synthesis cost Ls(p, Z) and the LiDAR cost C LI (p, Z). 
     Such a fusion can be expressed in an equation as given below. 
     Fourth Equation
 
 C ( p,Z )= A×C   LI ( p,Z )+ B×Ls ( p,Z )
 
     A: Coefficient (Weight) of LiDAR Cost 
     B: Coefficient (Weight) of Synthesis Cost Ls 
     The coefficients A and B determine whether the LiDAR costs are to strongly influence the fusion or the synthesis costs Ls(p, Z) are to strongly influence the fusion. As the LiDAR costs and the synthesis costs Ls(p, Z) have different desirable conditions that improve the level of precision, the coefficients A and B can be determined in an experimental manner. Alternatively, the coefficient A and the coefficient B may be set based on a table in which the coefficients A and B are determined in advance for different environmental conditions (e.g., a time zone, weather, and current location). As the stereo camera unit  120  performs object recognition on a reference image, a captured object can be identified for each area of reference image. Accordingly, the coefficient A and the coefficient B may be switched for each one of the areas. 
     Fusion by Pixel Replacement 
     A fusion that is performed by replacing pixels is described below. The fusion unit  29  replaces the distance to each pixel obtained by performing block matching with the distance data that is calculated based on the reflected signal. 
       FIG. 23  is a diagram illustrating pixel replacement according to the present embodiment. 
     One or more objects (or no object) may exist in the irradiation field  101  irradiated with one laser beam. It is expected that a peak is included in the reflected signal to be measured by the LiDAR range finder  110  as the laser beam is reflected by such one or more objects. Accordingly, when the reliability of the reflected signal is high, the accuracy of the distance to each pixel can be improved by replacing the distance to each pixel obtained by performing block matching with the distance as indicated by the peak. 
     As illustrated in  FIG. 23 , three peaks  102  to  104  are detected from a reflected signal, and it is assumed that the distance indicated by the peak  102 , which one of the peaks  102  to  104 , is La. Note that the distance La is calculated by the distance calculator  28 . When there is a pixel whose distance is close the distance La in the irradiation field  101 , it is expected that the distance to that pixel is equivalent to the distance La. For example, the fusion unit  29  compares the distances La to Lc that are calculated based on the reflected signal with the distance to each pixel of the irradiation field  101 , and the distance to each pixel obtained by performing block matching is replaced with the distance La when the distances La to Lc are equivalent to the distance to each pixel of the irradiation field  101 . In the example of  FIG. 23 , the distance of a pixel  10   a  on which a part of an object A is captured is replaced with the distance La. 
     By so doing, the distances of the pixels whose originally-indicated distances are equivalent to the distance La are flattened to the fixed distance La, and separation can easily be achieved by surface. 
     Instead of simply replacing the distance obtained by performing block matching with the distance that corresponds to a peak of a reflected signal, these distances may be weighted and combined. In other words, such a combined distance may be calculated as follows.
 
Combined Distance=α×Distance obtained by performing Block Matching+β×Distance corresponding to Peak of Reflected Signal
 
     Note that α+β=1. 
     For example, the fusion unit  29  determines α and β as follows. The fusion unit  29  assumes that the reliability of β is higher as the level of the peak is higher, and determines β based on the level of the peak of the reflected signal. α is calculated by “1-β.” In such a configuration, a table in which the peak levels of a reflected signal are associated with β is prepared. 
     Alternatively, the fusion unit  29  may assume that the reliability of the obtained distance is higher as the distance obtained in the block matching is smaller, and may determine α based on the distance. β is calculated by “1-α.” In such cases, a table in which the distance to each pixel is associated with α is prepared. 
     Alternatively, α and β may separately be determined in a similar manner, and α and β may be adjusted such that the sum of α and β becomes 1. For example, when α and β are determined to be 0.6 and 0.5, respectively, according to the table, (0.6+0.5)/1=1.1. Accordingly, for example, α and β are adjusted as follows.
 
α=0.6/1.1=0.55 β=0.5/1,1=0.45
 
     Due to the configurations as described above, a combined distance can be calculated based on the distance obtained by performing block matching and the reliability of the distance that corresponds to a peak of a reflected signal. 
     i. Performing Fusion based on Cost 
     Three methods are described below for a fusion (principle fusion) between the data obtained by the LiDAR range finder  110  that emits a laser beam of low laser-beam resolution and the data obtained by the stereo camera unit  120 . 
       FIG. 24  is a flowchart of how a fusion is performed based on a cost, according to the present embodiment. 
     The processes in  FIG. 24  are performed every time a pair of a reference image and a comparison image is captured. 
     Firstly, the stereo matching unit  23  performs block matching on a reference image and a comparison image to calculate the stereo-matching cost C ST , and further computes the distance on a pixel-by-pixel basis (step S 10 ). 
     The LiDAR range finder  110  emits a laser beam predetermined number of times while one reference image is being captured. Accordingly, the data acquisition unit  21  sequentially obtains the irradiation direction of one of the laser beams and a reflected signal from the LiDAR range finder  110  (step S 20 ). The following processes are performed for each laser pulse (for each irradiation field). 
     Subsequently, the pixel-range determination unit  31  determines the pixel range by obtaining the pixel range that is association with the irradiation direction in the irradiation-direction pixel-range table  32  (step S 30 ). 
     The distance calculator  28  determines the distance where the reflected signal takes a value equal to or greater than a threshold (step S 40 ). When there are three peaks that correspond to the objects A to C as illustrated in  FIG. 4 , the distances La, Lb, and Lc are determined. These distances La, Lb, and Lc are used in common in one pixel range. The following processes are performed based on each one of the distances La, Lb, and Lc. For the sake of explanatory convenience, description is given under the assumption that the focus is on the distance La. 
     Subsequently, the determination unit  27  determines whether a distance equivalent to the distance La falls within a pixel range (step S 50 ). Each of the pixels in the pixel range has the distance obtained by performing block matching. When one distance is equivalent to another distance, these two distances may be completely equal to each other, or these two distances may be slightly different from each other in a prescribed permissible range (for example, ±10%) with reference to the distance La. 
     When it is determined to be “NO” in the step S 50 , the process proceeds to a step S 90 , and the distance Lb subsequent to the distance La is processed in a similar manner. 
     When it is determined to be “YES” in the step S 50 , the distance interpolator  25  converts the disparity space of the stereo-matching cost C ST  of all the relevant pixels with distances equivalent to the distance La into a metric space (step S 60 ). 
     Subsequently, the reflected-signal cost converter  26  calculates the LiDAR cost C LI  of the single laser beam determined in the step S 30  (step S 70 ). 
     Subsequently, the fusion unit  29  performs fusion between the stereo-matching cost C ST  and the LiDAR cost Cu of all the pixels with distances equivalent to the distance La (step S 80 ). 
     The fusion unit  29  determines whether all the distances La to Lc where the reflected signal takes a value equal to or greater than a threshold have been processed (step S 90 ). When it is determined to be “NO” in the step S 90 , the process returns to the step S 50 , and the next distance Lb is processed. 
     When it is determined to be “YES” in the step S 90 , the fusion unit  29  determines whether all the reflected signals (i.e., all the pixel ranges) of the laser beam that is emitted to the single reference image have been processed (step S 100 ). When it is determined to be “NO” in the step S 100 , the process returns to the step S 30 . 
     When it is determined to be “YES” in the step S 100 , it is assumed that a fusion on one reference image is completed and the SGM unit  24  calculates and obtains a synthesis cost (step S 110 ). 
     Even when a laser beam of low laser-beam resolution is emitted, as described above, the fusion according to the present embodiment is performed and the planes of a plurality of objects existing in one pixel range, each of which indicates the distance, can be separated from each other by surface. 
     In the example embodiment as illustrated in  FIG. 24 , the SGM is performed after a fusion is performed. However, no limitation is indicated thereby, and the SGM may be performed before a fusion is performed. In such a configuration, for example, the SGM is performed subsequent to the step S 10 . Alternatively, the semi-global matching (SGM) may be omitted. 
     In the step S 40  of  FIG. 24 , a reflected signal with a value equal to or greater than a threshold is detected. However, a reflected signal may be digitally processed (e.g., analog-to-digital (A/D) conversion), and the distance of each peak may be extracted. In the steps S 50  to S 90 , these extracted distances are processed. 
     In the step S 80 , a fusion between a stereo-matching cost and a LiDAR cost is performed. a fusion between the stereo-matching cost and a reflected signal may be performed. 
     2. Replacement of Distance to Pixel obtained by performing Block Matching with Distance Data calculated based on Reflected Signal 
       FIG. 25  is a flowchart of how a fusion is performed as the distance to each pixel obtained by performing block matching is replaced with the distance data that is calculated based on the reflected signal, according to the present embodiment. 
     In the description of  FIG. 25 , only the differences from the processes in  FIG. 24  may be described. 
     The processes in the steps S 101  to S 104  in  FIG. 25  are equivalent to the processes in the steps S 10  to S 40  in  FIG. 24 , respectively. The following processes are performed for each one of the pixels in a certain pixel range. 
     Subsequent to the step S 104 , the determination unit  27  focuses on one of the pixels in a certain pixel range, and determines whether the distance that corresponds to the distance to a pixel, which is obtained by performing block matching, is calculated from a reflected signal in the step S 104  (step S 105 ). In other words, whether the distances La to Lc calculated in the step S 104  are equivalent to the distance to each pixel is determined. 
     When it is determined to be “NO” in the step S 105 , the process proceeds to a step S 107  in order to judge the next pixel. In other words, the fusion unit  29  does not replace the distance to each pixel obtained by performing block matching with the distance data that is calculated based on a reflected signal. 
     When it is determined to be “YES” in the step S 105 , the fusion unit  29  replaces the distance to a pixel of interest with the distance data that is calculated based on a reflected signal (step S 106 ). When the three distances La to Lc are calculated from a reflected signal, the distance to a pixel is replaced with one of the distances La to Lc. 
     Subsequently, the fusion unit  29  determines whether the processes are completed for all the pixels in one pixel range (step S 107 ). When it is determined to be “NO” in the step S 107 , the process returns to the step S 105  in order to perform a fusion on the next pixel. As described above, a fusion is performed on each one of the pixels existing in a pixel range. 
     When it is determined to be “YES” in the step S 107 , the fusion unit  29  determines whether the processes are completed for all the pixel ranges of one reference image (step S 108 ). When it is determined to be “NO” in the step S 108 , the process returns to the step S 103 . 
     When it is determined to be “YES” in the step S 109 , the SGM unit  24  calculates and obtains a synthesis cost (step S 110 ). 
     Even when a laser beam of low laser-beam resolution is emitted, as described above, the fusion according to the present embodiment is performed and the planes of a plurality of objects existing in one pixel range, each of which indicates the distance, can be separated from each other by surface. 
     3. Replacement of Distance to Pixel obtained by performing Block Matching with Distance Data calculated based on Reflected Signal 
     As a modification of the processes in  FIG. 25 , the procedure in which a fusion is performed after the SGM is performed is described below. 
       FIG. 26  is a flowchart of how a fusion is performed as the distance to each pixel obtained by performing block matching is replaced with the distance data that is calculated based on the reflected signal, according to the present embodiment. 
     In the description of  FIG. 26 , only the differences from the processes in  FIG. 25  may be described. 
     Subsequent to the step S 101 , as illustrated in  FIG. 26 , a synthesis cost is calculated in a step S 109  using the SGM. As described above, a fusion can be performed in a similar manner even when a synthesis cost is calculated before a fusion is performed. 
     Some advantageous effects of the distance-measuring apparatus  100  according to the present embodiment are described below with reference to  FIG. 27A  and  FIG. 27B . 
       FIG. 27A  and  FIG. 27B  are diagrams illustrating a scene in which the distance is measured by the distance-measuring apparatus  100  and a distance image are illustrated, respectively, according to the present embodiment. 
     As illustrated in  FIG. 27A , the distance-measuring apparatus  100  irradiates an irradiation field  101  including a person  301  and a high-reflection reflector  302  with a single laser beam. The distance to the person  301  is about 57 meters (m), and the distance to the high-reflection reflector  302  is about 147 m. In this situation, so-called multiple pulses in which a peak of the person  301  and a peak of the high-reflection reflector  302  are detected are obtained from a reflected signal. 
       FIG. 27B  is a diagram illustrating the distance image of the image data illustrated in  FIG. 27A . 
     The distance image as illustrated in  FIG. 27B  is obtained by performing a principle fusion in which the distance to each pixel obtained by performing block matching is replaced with the distance data that is calculated based on the reflected signal. In an actual configuration, the distance on a distance image is indicated by color. For the sake of explanatory convenience in drawing, the distances are indicated by hatching or the like in  FIG. 27B . The same kind of hatching indicates the same distance. 
     As illustrated in  FIG. 27B , the person  301  and the high-reflection reflector  302  are separated by different planes each of which indicates the distance. In other words, even in an occlusion area where a person and a high-reflection reflector overlaps with each other, the distance-measuring apparatus  100  according to the present embodiment can successfully separate the planes of objects by surface, each of which indicates the distance, with a correct distance value and a high degree of accuracy. 
     As described above, the distance-measuring apparatus  100  according to the present embodiment emits a laser beam of low laser-beam resolution. Due to such a configuration, space saving or cost reduction of the distance-measuring apparatus  100  can be achieved. Moreover, a principle fusion is performed between the data obtained by a stereo camera and the data obtained by a LiDAR device at an early stage. Accordingly, even when multiple pulses occur at a plurality of objects, the distance image can be separated from each other by surface. 
     Numerous additional modifications and variations are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims, the disclosure of the present invention may be practiced otherwise than as specifically described herein. For example, elements and/or features of different illustrative embodiments may be combined with each other and/or substituted for each other within the scope of this disclosure and appended claims. 
     In the embodiment described above, cases in which the stereo-matching cost C ST  of each pixel is calculated are described. However, no limitation is indicated thereby, and a stereo-matching cost C ST  may be calculated for every pixel area. Even when a stereo-matching cost C ST  is calculated for every pixel area, the distance to each pixel is set. 
     In the embodiment as described above, cases in which the stereo camera unit  120  and the LiDAR range finder  110  are formed as a single integrated unit are described. However, the LiDAR range finder  110  and the stereo camera unit  120  may be configured separately. 
     In the embodiment as described above, the laser signal processor  240  mainly extracts a peak from an analog signal, and the stereo image computation unit  250  handles a digital signal. However, no limitation is indicated thereby, and immediately after the light-receiving element  235  receives a reflected signal, the laser signal processor  240  may convert the obtained reflected signal into a digital signal and may extract a peak from the obtained digital signal. 
     In the embodiment as described above, each of the stereo image computation unit  250  and the laser signal processor  240  is configured by a dedicated integrated circuit. However, for example, a recording medium storing the program codes of software that implements the functions of the stereo image computation unit  250  and the laser signal processor  240  may be provided for an information processing apparatus to implement the functions of the stereo image computation unit  250  and the laser signal processor  240 . 
     In the embodiment as described above, cases in which the distance-measuring apparatus  100  is installed in the vehicle  140  are described. However, the distance-measuring apparatus  100  may be installed, for example, in a motorbike, a bicycle, a wheelchair, and an agricultural cultivator. Alternatively, the distance-measuring apparatus  100  may be installed in a mobile object such as an autonomous mobile robot, a flight vehicle such as a drone, or an industrial robot that is disposed in a fixed manner in factory automation (FA). 
     At least some of the block matching operation may be performed by the ECU  190 , and some of the operation of the ECU  190  may be performed by the stereo image computation unit  250 . 
     Note also that the stereo matching unit  23  is an example of a converter, and the laser beam source  232  and the projector lens  233  are an example of an irradiation unit. The light-receptive lens  234  and the light-receiving element  235  are an example of a light receiver, and the distance calculator  28  is an example of a distance calculator. The fusion unit  29  is an example of an integration unit, and the distance that is converted by the stereo matching unit  23  by performing block matching is an example of first distance information. The distance information that is calculated by the distance calculator  28  is an example of second distance information. 
     Each of the functions of the described embodiments may be implemented by one or more processing circuits or circuitry. Processing circuitry includes a programmed processor, as a processor includes circuitry. A processing circuit also includes devices such as an application specific integrated circuit (ASIC), digital signal processor (DSP), field programmable gate array (FPGA), and conventional circuit components arranged to perform the recited functions.