Patent Publication Number: US-8983124-B2

Title: Moving body positioning device

Description:
TECHNICAL FIELD 
     The present invention relates to a moving body positioning device serving as an essential element for monitoring and tracking a moving body, which moving body positioning device uses an external monitoring camera. 
     BACKGROUND ART 
     A technology for measuring a position and direction specialized in walking movements of a human being as a pedestrian, with use of self-contained sensors (e.g. acceleration, gyro, magnetic, pressure sensors) worn on the hips, toes and the like of the human being is called Pedestrian Dead Reckoning (PDR), and has been well studied from the past (Non Patent Literature 1). 
     In PDR, outputs of the self-contained sensors are analyzed in view of constraints in the walking movements of the human being, and a motion vector or a motion velocity vector of the pedestrian is estimated one by one and are accumulated. 
     CITATION LIST 
     Non Patent Literature 
     Non Patent Literature 1 
     Masakatsu Kourogi, Takashi Okuma, Takeshi Kurata, “ Hokosha Nabi no tame no Jizo Sensa Moju - ru wo Mochiita Okunaisokui Shisutemu to sono Hyoka ” (Indoor positioning system using self-contained sensor modules for pedestrian navigation, and its evaluation), Symposium “Mobile 08” Reviews, pp. 151-156, 2008 
     Non Patent Literature 2 
     E. Foxlin, “Pedestrian Tracking with Shoe-Mounted Inertial Sensors”, IEEE Computer Graphics and Applications, vol. 25, no. 6, pp. 38-46, 2005. 
     Non Patent Literature 3 
     Tomoya Ishikawa, Thangamani Kalaivani, Masakatsu Kourogi, Andrew P. Gee, Walterio Mayol, Keechul Jung, Takeshi Kurata, “ Kamera to Jizo Sensa Moju - ru wo heiyou shita Intarakuthibu  3  jigen Okunai Kankyou Modera ” (Interactive three-dimensional indoor environment modeler with use of a camera and self-contained sensor module), Nihon VR Gakkai Kenkyu Houkoku, Vol. 14, CS-3, pp. 65-70, 2009 
     Non Patent Literature 4 
     Taniguchi, Nishio, Toriyama, Babaguchi, Hagita, “ Kanshi Kamera Eizou ni okeru GPS Tanmatsu Keitai Yu - za no Doutei to Tsuiseki  (Identification and tracking of GPS terminal portable user in a monitoring camera image), Johoshorigakkai CVIM Kenkyu Houkoku, 2006-CVIM-153, pp. 315-320, 2006 
     SUMMARY OF INVENTION 
     Technical Problem 
     In relation to technical development of PDR, the following issues are to be further solved in order to make PDR more practical. 
     A first problem is that in a position/direction measurement device based on PDR, its measurement error gradually accumulates in the course of motion. 
     Secondly, as also described in Non Patent Literature 1, with PDR, motion velocity estimated based on individual difference between pedestrians vary by a certain degree, and it is necessary to find an individual difference parameter to appropriately correct this variation. It is possible to estimate an individual difference parameter by having the pedestrian carry out a calibration operation in advance; this procedure is complex however, and serves as a problem in practical use. 
     Thirdly, in solving the first and second problems based on the image captured by the monitoring camera, a human figure inside the image captured by the monitoring camera needs to be associated with the human figure that the PDR is tracking. However, with the techniques currently available, it is difficult to steadily achieve such an associated state. 
     An object of the present invention is to provide a moving body positioning device serving as an essential element when monitoring and tracking a moving body, which moving body positioning device is accomplished to solve such problems and which uses an external monitoring camera. 
     Solution to Problem 
     In order to attain such an object, the moving body positioning device according to the present invention solves the first problem of the accumulation of measurement error by PDR, by correcting a PDR measurement result by combining (i) an analysis result of an image obtained by a monitoring camera externally provided, with (ii) the PDR measurement result. Namely, a human figure inside the image of the monitoring camera is made associated with the human figure that PDR is to track, and a position of PDR is corrected to a position of the human figure in the image of the monitoring camera. 
     Moreover, regarding the second problem of estimating the individual difference parameters of a pedestrian, the moving body positioning device according to the present invention is capable of tracking a position of a human figure in the image by analyzing the image of the monitoring camera, and estimating its motion velocity vector. Hence, the individual difference parameter is estimated by analyzing this result and PDR sensor data. 
     Moreover, the moving body positioning device according to the present invention solves the third problem of associating the human figure in the image of the monitoring camera with the human figure that the PDR tracks by following procedures described below. Namely, first, an image of a monitoring camera whose location relationship with a floor surface on which a pedestrian moves is well known is analyzed, to allow focusing on a difference image with the background. Thereafter, a human figure image in the foreground is cut out, and positions of the head and feet of that human figure are estimated. Next, by tracking the position of the feet one by one, a motion velocity vector or a motion vector is estimated. This motion velocity vector or motion vector is collated with a motion velocity vector or a motion vector that the PDR outputs, to associate the PDR output with the human figure that the monitoring camera tracks. 
     As a configuration of the present invention, a moving body positioning device of the present invention includes: an internal observation device provided to a moving body, to measure and output a motion of the moving body; an internal observation data processing device that estimates a motion of the moving body based on the output from the internal observation device; an external observation device that observes motion of a plurality of moving bodies; an external observation data processing device that estimates a motion of the moving body from an observation result by the external observation device; and a collation processing device that collates an output from the internal observation data processing device with that of the external observation data processing device, and outputs its collation result as a TRUE signal or a FALSE signal. 
     More specifically, the moving body positioning device according to the present invention includes: a self-contained sensor group that outputs a motion velocity vector of the moving body with use of an acceleration sensor provided in the moving body; a motion velocity vector estimation processing device that measures a motion velocity vector based on the output of the self-contained sensor group, and outputs an output sequence of the motion velocity vector together with a measured time; a monitoring camera for externally image capturing the moving bodies; an image analysis processing device that analyzes an image of the monitoring camera to measure a position of feet of the moving body in the image to measure a motion velocity vector of that position of the feet, and outputs an output sequence of the motion velocity vector together with a measured time, and a motion velocity vector collation processing device that collates the output sequence of the motion velocity vector estimation processing device with the output sequence of the image analysis processing device, and outputs its collation result as a TRUE signal or a FALSE signal. 
     Moreover, the moving body positioning device according to the present invention includes, as its configuration: a self-contained sensor group that outputs a motion vector of the moving body, the motion vector being obtained by integrating a motion velocity vector with use of an acceleration sensor provided in the moving body; a motion vector estimation processing device that measures a motion vector based on an output of the self-contained sensor group and outputs an output sequence of the motion vector together with a measured time; a monitoring camera for externally image capturing the moving bodies; an image analysis processing device that analyzes an image of the monitoring camera to measure a position of feet of the moving body in the image to measure a motion vector of that position of the feet, and outputs an output sequence of the motion vector together with a measured time; and a motion vector collation processing device that collates the output sequence of the motion vector estimation processing device with the output sequence of the image analysis processing device, and outputs its collation result as a TRUE signal or a FALSE signal. 
     Moreover, the moving body positioning device according to the present invention includes, as its configuration: a self-contained sensor group that outputs a motion vector of the moving body, the motion vector being obtained by integrating a motion velocity vector with use of an acceleration sensor provided in the moving body; a self-contained sensor base motion identification processing device that identifies a movement kind of the moving body in accordance with an output of the self-contained sensor group, and outputs an identification result together with a measured time; a monitoring camera for externally image capturing the moving bodies; an image analysis processing device that analyzes an image of the monitoring camera to identify the movement kind of the moving body in the image and outputs its identification result together with a measured time; and the collation processing device is a movement kind collation processing device that collates the output of the self-contained sensor base motion identification processing device with the output of the image analysis processing device, and outputs its collation result as a TRUE signal or a FALSE signal. 
     Moreover, in the moving body positioning device according to the present invention, when the motion velocity vector collation processing device collates the output sequence from the motion velocity vector estimation processing device with the output sequence from the image analysis processing device, the motion velocity vector collation processing device determines a weighting factor in accordance with a size of an area of a unit pixel of the image of the monitoring camera projected on a floor surface at the position of the feet of the moving body estimated from the image of the monitoring camera, to carry out the collation process. This is similarly carried out in a case in which the motion vector collation processing device collates the output sequence from the motion vector estimation processing device with the output sequence from the image analysis processing device. Moreover, in this case, in the collation process, the weighting factor is made smaller as the area of the unit pixel is projected larger, and the weighting factor is made larger as the area of the unit pixel is projected smaller. 
     Moreover, as another feature, the moving body positioning device of the present invention further includes a position correction signal output device, when the motion velocity vector collation processing device outputs the TRUE signal, the position correction signal output device outputting a signal that corrects a positional coordinate of the moving body to a position of the moving body wearing the self-contained sensor group, the positional coordinate being outputted from the image analysis processing device. 
     As yet another feature, the moving body positioning device of the present invention further includes a walking parameter estimation processing device, the motion velocity vector estimation processing device correcting and outputting the output sequence of the motion velocity vector in accordance with an individual difference parameter set in advance, and when the motion velocity vector collation processing device outputs the TRUE signal, the walking parameter estimation processing device resetting the individual difference parameter in the motion velocity vector estimation processing device with use of pair information of time series data of a collated motion velocity vector and an output sequence of sensor data of the self-contained sensor. 
     Moreover, the moving body positioning device according to the present invention further includes an identification information storage/display device that stores and displays identification information identifying the moving body, when the motion velocity vector collation processing device outputs the TRUE signal, the identification information storage/display device storing and displaying, as information indicative of the moving body in the image of the monitoring camera, the identification information of a moving body that wears the self-contained sensor, and when the motion velocity vector collation processing device outputs the FALSE signal, the identification information storage/display device storing and displaying, as information indicative of the moving body in the image of the monitoring camera, the identification information indicating that no self-contained sensor is worn. 
     Advantageous Effects of Invention 
     With use of the moving body positioning device of the present invention including the foregoing features, when a person (moving body) wearing for example PDR sensors (an internal observation device and a self-contained sensor group of positioning devices) enters into an image of for example a monitoring camera (an external observation device), an estimation result of a position of the wearing person (moving body) can be corrected based on an analysis result of that image. Hence, no measurement error of the position/direction caused by the PDR is accumulated together with movement of the moving body, as like in the conventional art. 
     Moreover, by using the moving body positioning device of the present invention, in a case in which a person wearing for example the PDR sensors (an internal observation device and a self-contained sensor group of the positioning device) is in the image of for example the monitoring camera (an external observation device), it is possible to estimate a motion velocity of the wearing person (moving body) based on that image. By associating this with the PDR sensor data based on this result, it is possible to estimate an individual difference parameter of the wearing person. With use of this estimated individual difference parameter, it is possible to carry out a calibration operation in advance. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a view schematically illustrating a moving body positioning device according to the present invention. 
         FIG. 2  is a block diagram illustrating basic processing elements of the moving body positioning device according to the present invention. 
         FIG. 3  is a view illustrating another embodiment of the moving body positioning device according to the present invention. 
         FIG. 4  is a block diagram illustrating a configuration of another embodiment of the moving body positioning device according to the present invention. 
         FIG. 5  is a block diagram illustrating a configuration of another embodiment of the moving body positioning device according to the present invention. 
         FIG. 6  is a block diagram illustrating a configuration of another embodiment of the moving body positioning device according to the present invention. 
         FIG. 7  is a flowchart describing a series of processes for setting a weighting factor in a collation process carried out by a motion velocity vector collation processing device or a motion vector collation processing device. 
         FIG. 8  is a block diagram illustrating a configuration of another embodiment of the moving body positioning device of the present invention. 
         FIG. 9  is a block diagram illustrating a configuration of another embodiment of the moving body positioning device of the present invention. 
         FIG. 10  is a block diagram illustrating a configuration of another embodiment of the moving body positioning device of the present invention. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     Described below is an embodiment of a moving body positioning device of the present invention, with reference to drawings.  FIG. 1  is a view schematically illustrating a moving body positioning device according to the present invention, and  FIG. 2  is a block diagram illustrating a configuration of basic processing elements of the moving body positioning device according to the present invention. 
     An external observation device  11  in  FIG. 1  is a device that can observe movements of a plurality of moving bodies in a predetermined space (external world) such as a road, an open space, a surface of the ocean or the like. Examples of the external observation device  11  include a monitoring camera, a Z-value sensor, a laser range finder and the like. An internal observation device  12  is a device worn on a moving body, and measures motion of the moving body. Examples of the internal observation device  12  are combinations of (i) a sensor that measures movement such as an acceleration sensor, a magnetic sensor, an angular velocity sensor, or a pressure sensor and (ii) a clock. As the sensor that measures movement, a temperature sensor may be combined with the acceleration sensor, the magnetic sensor, the angular velocity sensor, or the pressure sensor. Examples of the moving body encompass a pedestrian, a bicycle, an automobile, an airplane, and a ship. 
     The external observation device  11  observes each of moving bodies wearing the internal observation device  12  (in the example of  FIG. 1 , a moving body  2  being a pedestrian) and a moving body  1  (similarly in this example, a pedestrian) not wearing the internal observation device  12  or not sending out information of the internal observation device  12  although the moving body is wearing the internal observation device  12 . At this time, movement of each of the plurality of moving bodies that is to be observed is estimated for every discrete time based on a motion velocity vector, motion vector, motion identification and the like. 
     For example, when the external observation device  11  is a monitoring camera that image captures a moving body, the movement of the moving body can be estimated by tracing the moving body in the image of the monitoring camera as appropriate by its shape, color and the like, and combining this with a motion velocity vector estimation processing device that estimates a motion velocity vector of the moving body. 
     Moreover, the movement of the moving body can be estimated by use of a sensor that measures a depth (Z value) of the external world as the external observation device  11 , and combining this with a Z-value analysis device that detects a moving body which is the subject to be image captured and estimates its motion velocity vector depending on its depth. The sensor for measuring the Z value may be a depth measurement device using a stereo camera in a case of a passive sensor, and may be a device which measures a distance (Z-value) by emitting infrared light and measuring a time required for the infrared light to reflect back, in a case of an active sensor. 
     Alternatively, the movement of the moving body can be estimated by using a Laser Range Finder (LRF) as the external observation device  11 , which LRF emits a laser beam to the external world and measures a distance from the moving body based on its reflected light, and combine therewith an analysis device that detects the moving body based on the measurement result of that distance and estimates its motion velocity vector. 
     Meanwhile, the internal observation device  12  estimates the movement of the moving body that wears the internal observation device  12 , for every discrete time based on the motion velocity vector, the motion vector, the motion identification and the like. Time series data of the motion velocity vector observed in each of the external world and the internal world is collected to one location by communications means (e.g., with use of wireless data communications network). At that location, a collation process (A) is carried out to the time series data of the motion velocity vector of at least one of the moving bodies that the external observation device  11  captures, with the motion velocity vector outputted by the internal observation device  12 , and when the collation is successful and is deemed as a time series of a motion velocity vector of an identical moving body, a TRUE signal is outputted, and for any other cases, a FALSE signal is outputted. 
       FIG. 2  is a block diagram illustrating a configuration of basic processing elements in the moving body positioning device according to the present invention. The external observation device  21  is a device similar to the external observation device  11  of  FIG. 1 , and detects at least one moving body and outputs its result together with time data. Output data  30  differs depending on a used external observation device; for example, when a camera is used, the output data  30  is image data with time, when the Z-value sensor is used, the output data  30  is a collection of Z values with time, and when the laser range finder is used, the output data  30  is a collection of distance data with time. An external observation data processing device  24  is a device that detects a moving body based on the output data  30  and outputs time series data of its motion velocity vector, motion vector, or motion identification result of the moving body; more specifically, is a computer including a memory, a processor, and an input/output interface. This can be achieved by, for example, a process of detecting a subject moving body (e.g. a human figure) based on features such as shape and color, in image analysis. 
     The internal observation device  22  is, as illustrated in  FIG. 1 , a device that is worn on a moving body to measure its motion, similarly to the internal observation device  21  of  FIG. 1 . The internal observation device  22  is achievable by, for example, use of a self-contained sensor (a combination of acceleration, magnetic, angular velocity, pressure, and temperature sensor) with a clock (real-time clock, etc.). The internal observation data processing device  23  is a device which, in a case in which the motion velocity vector is to be estimated, obtains an acceleration vector fixed to a (three-dimensional) world coordinate system based on a time-attached output from the self-contained sensor, and estimates the motion velocity vector by its acceleration integral, and more specifically is a computer having a memory, a processor, and an input/output interface. Moreover, in a case in which the moving body is limited to just pedestrians, it is achievable by estimating the motion velocity vector by the method of PDR (Pedestrian Dead Reckoning). The internal observation data processing device  23  outputs time series data ( 33 ) of the motion velocity vector or motion vector of the moving body wearing the internal observation device  22 , or a motion identification result of the moving body. 
     Finally, the collation processing device  25  collates (a) the time series data ( 31 ) of the motion velocity vector, motion vector, or motion identification result of the moving body related to one moving body obtained based on the external observation device  21  with (b) the time series data ( 33 ) of the motion velocity vector, motion vector or motion identification result of the moving body obtained based on the internal observation device  22 , and in a case in which the two can be collated, the collation processing device  25  outputs a TRUE signal, and in other cases, outputs a FALSE signal ( 34 ). Moreover, the collation processing device  25  is also a computer including a memory, a processor, and an input/output interface, and carries out the collation process of data received from the external observation data processing device and the internal observation data processing device with use of the processor. 
     For example, in a case of collating the time series data of the motion velocity vector, a distance scale between the time series data of the motion velocity vectors is set beforehand based on the time series data ( 31 ) of the motion velocity vector and the time series data ( 33 ) of the motion velocity vector obtained in accordance with the internal observation device  22 ; when this distance scale is not more than a set threshold, the two motion velocity vectors are determined as being collated and thus a TRUE signal is outputted, whereas in any other case, a FALSE signal is outputted ( 34 ). Note that, as the distance scale described before, a distance scale that allows for a certain jitter (time difference) to be present in the time data held by the two time series data is selected and used. 
       FIG. 3  illustrates a state in which a monitoring camera  101  is provided in a known disposition relationship with the floor surface, and the image captured by the monitoring camera  101  includes a path, an open space or the like where people often pass. The self-contained sensor  102  is a collection of sensors that can operate without external infrastructure; as the self-contained sensor  102 , an acceleration sensor, a gyro sensor, a magnetic sensor, a pressure sensor or the like may be used for example. 
     Here, with the monitoring camera  101 , when an environment model is generated upon appropriately setting a scale, a translation and rotation movement parameter with respect to an external environment in which the monitoring camera  101  is provided and a camera parameter constituted of a focus distance and scale coefficient are found by carrying out the following procedures. Such an environment model can be generated interactively by executing a modeler application program (modeler application) with use of a method described in Non Patent Literature 3 or the like. As described in Non Patent Literature 3, procedures are carried out for finding a vanishing point in the environment based on an instruction by the user, with use of the modeler application described before (more specifically, the user selects a pair of two parallel straight lines in the environment). 
       FIG. 3  illustrates a state in which a pedestrian, who is a moving body wearing the self-contained sensor  102 , is detected as being included and moving in the image of the monitoring camera  101 , and a process (A) of collating the human figure in the image of the monitoring camera  101  with the pedestrian wearing the self-contained sensor  102  is carried out. 
     In  FIG. 4 ,  201  is a monitoring camera,  202  is a self-contained sensor group,  203  is a motion velocity vector estimation processing device,  204  is an image analysis processing device, and  205  is a motion velocity vector collation processing device. With the configuration including these processing components, the image of the monitoring camera is collated with the output of the self-contained sensor, to output a TRUE or a FALSE signal. 
     The image (frame image of each time) captured by the monitoring camera  201  is outputted to the image analysis processing device  204 . Here, candidates of figures of the human figure of the moving body is selected, positions of their feet are estimated, and motion velocity vector of each time is estimated by time integrals of the positions, to output an output sequence of the motion velocity vector. Note that the estimation of the motion velocity vector can be carried out by obtaining data with, instead of the monitoring camera, a depth measurement device with use of a stereo camera, or a laser range finder. Hereinafter, the moving body is described as a human figure. 
     In the embodiment,  210  is information of each of frame images of the image of the monitoring camera, and  211  is information of a result of analyzing the frame images. In a case in which a human figure is present in the image, data indicative of a positional coordinate of a floor surface on which the feet of the human figure is present is outputted as the information  211  of the analysis result, and in a case in which no human figure is included, data indicative of a signal of that fact is outputted as the information  211  of the analysis result. 
     On the other hand, the output data  212  of the self-contained sensor group  202  is outputted to the motion velocity vector estimation processing device  203 ; based on the output data (acceleration vector, angular velocity vector, magnetic vector, pressure data) of the self-contained sensor group  202 , the motion velocity vector of the wearing person (human figure) for each of the times is estimated. 
     The output data  212  is, as described above, an output of sensor data from the sensor included in the self-contained sensor group  202 . The self-contained sensor group  202  includes a timer, and an acceleration vector, angular velocity vector, magnetic vector, and pressure data, each having time stamp information obtained by the timer, are outputted from the self-contained sensor group  202 . Calculation of the motion velocity vector based on the sensor data of the output data  212  of the self-contained sensor group  202  is, for example, carried out by processing data in the method described in Non Patent Literature 1. Data  213  outputted from the motion velocity vector estimation processing device  203  is data of an output sequence of a motion velocity vector of a moving body (human figure) that wears the self-contained sensor group  202 . 
     The motion velocity vector collation device  205  accumulates the output sequences of the motion velocity vector outputted from the image analysis processing device  204  and the output sequences of the motion velocity vector outputted from the motion velocity vector estimation processing device  203  for a certain time and compares the two, to determine whether or not these output sequences match each other. The data processing of this determination is, as disclosed in Non Patent Literature 4, a data processing in which a total of magnitudes of a difference vector between the two motion velocity vectors are calculated and thereafter this total is normalized with a length of time or a sample number; the normalized total is compared with a predetermined threshold, and is determined as being collated in the case in which the normalized total is not more than the threshold. 
     The time series data of the motion velocity vector estimated by the motion velocity vector estimation processing device  203  based on the sensor data of the self-contained sensor group  202  is collated with the motion velocity vector estimated from the positional coordinates of the feet of the human figure in the image obtained as an analysis result of the frame images from the monitoring camera  201  by the image analysis processing device  204 , and as its result, in a case in which the two collate with each other, a signal indicative of TRUE is outputted as the output data  214  outputted from the motion velocity vector collation device  205 , and in a case in which the two do not collate with each other, a signal indicative of FALSE is outputted as the output data  214  outputted from the motion velocity vector collation device  205 . 
     The moving body positioning device of the embodiment described above carries out the collation process based on the output sequence of the motion velocity vector, however it is also possible to carry out the collation process based on a motion vector (i.e. relative positional vector) instead of collating with the motion velocity vector. An embodiment with such a configuration is described below. 
       FIG. 5  is a block diagram describing a configuration of another embodiment of the moving body positioning device of the present invention. In  FIG. 5 ,  301  is a monitoring camera,  302  is a self-contained sensor group,  303  is a motion vector estimation processing device,  304  is an image analysis processing device, and  305  is a motion vector collation processing device. The monitoring camera  301  is as with the monitoring camera  201  in  FIG. 4 . The monitoring camera  301  outputs a frame image signal  310 . The image analysis processing device  304 , upon receiving the frame image signal  310  and determining that a human figure (moving body) is present inside the frame image, outputs an output sequence of the motion vector  311  of that human figure. 
     On the other hand, the self-contained sensor group  302  is as with the self-contained sensor group  202  in  FIG. 4 . The output data  312  outputted from the self-contained sensor group  302  is an output sequence of sensor data such as an acceleration vector, an angular velocity vector, a magnetic vector, and pressure data, each to which a time stamp is added. The motion vector estimation processing device  303 , when receiving such sensor data of the output data  312  from the self-contained sensor group  302  as its input, estimates and outputs a relative motion vector of a person (moving body) wearing the self-contained sensor based on data processing such as carrying out integral processing of a velocity vector. For such estimation processing of a motion vector, it is possible to utilize, for example, data processing of calculating the motion vector by estimating a motion velocity and carrying out first order integral related to that time, as described in Non Patent Literature 1, and so thus the data processing of this method is used. The motion vector estimation processing device  303  outputs output data  313  of the output sequence of the calculated relative motion velocity vector. 
     The motion vector collation processing device  305  collates the time series data of the output data  311  of the motion vector obtained by the image analysis processing with the time series data of the output data  313  of the relative motion vector obtained by the motion vector estimation processing based on the sensor data. The time series data of the two motion vectors are collated by performing a collation process in which a total of magnitudes of difference vectors between the two motion vectors is calculated and its total is normalized with a length of time or a sample number, thereafter the normalized total is compared with a predetermined threshold and is determined as being collated in a case in which the normalized total is not more than that threshold. As a result of such a process, the motion vector collation processing device  305  outputs, as the output data  314 , a TRUE signal in a case in which it is determined as collated, and a FALSE signal in any other cases. 
     In the image analysis processing of the image analysis processing device  304  in this case, a detection accuracy of a position based on an image of the monitoring camera  301  when a human figure is included in the image as a small size decreases as compared to a case in which the human figure is included in the image as a large size. This means that when a unit pixel of the monitoring camera is back projected on the floor surface, the reliability changes in inverse proportion to its area. Hence, the motion vector collation processing device  305 , when the output sequence from the motion vector estimation processing device  303  collates with the output sequence from the image analysis processing device  304 , carries out the collation processing upon determining a weighting factor in accordance with an area of the unit pixel of the image of the monitoring camera projected on the floor surface at the position of the feet of the moving body estimated from the image of the monitoring camera. 
     In this case, in the collation processing, the weighting factor is made smaller as the area of the unit pixel is projected larger, and the weighting factor is made greater as the area of the unit pixel is projected smaller. Such a process can be similarly carried out in the embodiment of the moving body positioning device described with reference to  FIG. 4 . Namely, in this case, the motion velocity vector collation processing device  205 , when the output sequence from the motion velocity vector estimation processing device  203  is collated with the output sequence from the image analysis processing device  204 , carries out the collation upon determining the weighting factor in response to an area of the unit pixel of the image of the monitoring camera projected on the floor surface of the position of the feet of the moving body estimated from the image of the monitoring camera. 
       FIG. 6  is a block diagram describing a configuration of another embodiment of the moving body positioning device of the present invention. The embodiment described in  FIG. 6  is an embodiment in which, based on observation data by the internal observation device and external observation device, a self-contained base movement kind processing device, which is the internal observation data processing device, and an image analysis processing device, which is the external observation data processing device, identify a movement kind of the moving body, and collates the time series data of the identification result in the collation processing device. 
     In  FIG. 6 ,  3201  is a monitoring camera,  3202  is a self-contained sensor group,  3203  is a self-contained base movement kind processing device,  3204  is an image analysis processing device (motion type processing device), and  3205  is a movement kind collation processing device. The monitoring camera  3201  corresponds to the external observation device  21  in  FIG. 2 , and is as with the monitoring cameras  201  and  301 . The monitoring camera  3201  outputs a time-attached image signal  3210 . The image analysis processing device (movement kind processing device)  3204  receives the time-attached image signal  3210  as input, analyzes the movement of the moving body (human figure or the like) included in the image, and recognizes and identifies movements thereof. Several methods of known image processing and computer vision such as HMM (Hidden Markov Model) are available as methods of recognizing the movement kinds of the human figure, and recognition may be achieved by use of this method. Upon identifying the movement kind of the moving body, its identification result  3211  of the movement kind is outputted. 
     On the other hand, the self-contained sensor group  3202  corresponds to the internal observation device  22  in  FIG. 2 , and is as with the self-contained sensor groups  202  and  302 . The output data  3212  outputted from the self-contained sensor group  3202  is an output sequence of sensor data such as an acceleration vector, an angular velocity vector, a magnetic vector, pressure data, temperature data, each to which a time stamp is attached. 
     The self-contained base movement kind processing device  3203  identifies and recognizes a movement kind of the person wearing the self-contained sensor group  3202 , based on the output data  3212 . Such a movement kind processing device, for example, calculates (i) features vector of a time region of time series data such as the acceleration vector and the angular velocity vector that are part of the output from the self-contained sensor group, and (ii) features vector in a frequency region of the time series data converted by Fourier transformation. The movement kinds corresponding to the combination of the two features vectors, of the time region and of the frequency region, can be identified and recognized by a method of machine learning with use of a calculator. Examples of frameworks of the machine learning include AdaBoost (Adaptive Boosting), DP (Dynamic Programming) matching, and SVM (Support Vector Machine); by collating the received time series sensor data with learnt models or role model data with use of results of the machine learning of the data collected beforehand or actively collected by such a framework, it is possible to add to the input sensor data a specific identification result. By use of this method, it is possible to output ( 3213 ) time series data of an identification result of the movement kind. 
     The movement kind collation processing device  3205  corresponds to the collation processing device  25  in  FIG. 2 , and collates time series data of the two movement kind recognition results based on the output  3211  of the motion type processing device  3204  and the output  3213  of the self-contained base movement kind processing device  3203 . At this time, a distance scale between the time scale movement kind recognition result data is defined, and when this distance is not more than a set threshold, a TRUE signal is outputted as the two time series data being collated to each other, and in any other case, a FALSE signal is outputted ( 3214 ). 
       FIG. 7  is a flow chart describing processes of setting a weighting factor in the collation process carried out by the motion velocity vector collation processing device or the motion vector collation processing device. These processes are described below, with reference to  FIG. 7 . In this process, a position on the floor surface on which the human figure is present is found in the image of the monitoring camera in step S 401 , and subsequently in step S 402 , an area of which the unit pixel of the monitoring camera is projected on the floor surface on which the human figure is present is calculated. Thereafter, in the subsequent step S 403 , the weighting factor at that position is determined in accordance with the area calculated, and in step S 404 , the weighting factors for each of points on its trail is stored. The weighting factors are determined as such, to carry out the collation process. 
     Moreover, the moving body positioning device of the present invention may be modified so that an individual difference parameter is set, thereby allowing for improving the accuracy of the data processing in the estimation process. In this case, when the image of the monitoring camera is collated with the output of the self-contained sensor, the individual difference parameter is set by estimating an individual difference parameter that would characterize a walking movement of the human figure wearing the self-contained sensor, with use of the motion velocity vector of the human figure in the image and the output sequence of the self-contained sensor. 
     When the motion velocity vector or the motion vector of the human figure inside the image of the monitoring camera is associated with the motion velocity vector or the motion vector estimated in accordance with sensor data based on the self-contained sensor group, it is possible to associate the output sequence of the motion velocity vector of the human figure in the image of the monitoring camera with the output sequence of the sensor data of the self-contained sensor group. Accordingly, as also described in Non Patent Literature 1, for example, amplitude data of an acceleration component obtained by decomposing the output of the acceleration sensor in a vertical direction is associated with a magnitude of the motion velocity vector of the human figure in the image, to estimate an individual difference parameter (in the embodiment, a slope and intercept that determine a straight line) of that human figure (i.e. person wearing the self-contained sensor group). 
     Such an embodiment is described with reference to  FIG. 8 .  FIG. 8  is a block diagram illustrating a configuration of another embodiment of the moving body positioning device according to the present invention. In  FIG. 8 ,  201  is a monitoring camera,  202  is a self-contained sensor group,  203  is a motion velocity vector estimation processing device,  204  is an image analysis processing device, and  205  is a motion velocity vector collation processing device. These components are as with those described with reference to  FIG. 2 . In the embodiment, the configuration further includes a walking parameter estimation processing device  505 . 
     The walking parameter estimation processing device  505  receives the sensor data  503  outputted from the self-contained sensor group  202 , the motion velocity vector  501  of the position of the feet of the human figure inside the image, outputted from the image analysis processing device  204 , and further the output signal  502  of a collation result (TRUE/FALSE) outputted as a result of the collation process by the motion velocity vector collation processing device  205 , and estimates and outputs a walking parameter. The estimated output of the walking parameter is inputted into the motion velocity vector estimation processing device  203 , and is used when the motion velocity vector estimation processing device  203  carries out the estimation process of the motion velocity vector. 
     Namely, the process of estimating the walking parameter carried out by the walking parameter estimation processing device  505  is a process in which, when the motion velocity vector of the human figure in the image is collated with the motion velocity vector based on the sensor data of the self-contained sensor (i.e. when the signal  502  is a TRUE signal), the walking parameter estimation processing device estimates, based on the sensor data  503  of the self-contained sensor data and the motion velocity vector  501  associated at that time, a walking parameter characterizing the walking movement of the person wearing the self-contained sensor, and outputs the data of that walking parameter. The outputted walking parameter characterizing the individual difference is, as described above, used when the motion velocity vector estimation processing device  203  carries out the estimation process of the motion velocity vector. 
     The walking parameter estimation processing device  505  provided in the moving body positioning device illustrated in  FIG. 8  resets the walking parameter of the individual difference parameter in the motion velocity vector estimation processing device  203  when the motion velocity vector collation processing device  205  outputs a TRUE signal as the output data  214  of the collation process, with use of pair information of time series data of the collated motion velocity vector and the output sequence of sensor data of the self-contained sensor. Hence, the motion velocity vector estimation processing device  203  corrects and outputs the output sequence of the motion velocity vector, in accordance with the walking parameter of the set individual difference parameter. 
     Moreover, the moving body positioning device according to the present invention may be modified so that when the image of the monitoring camera is collated with the output of the self-contained sensor, identification information of the person wearing the self-contained sensor is associated with the human figure in the image, and this identification information is stored and displayed. An embodiment of such a configuration is described with reference to  FIG. 9 . 
       FIG. 9  is a block diagram illustrating a configuration of another embodiment of the moving body positioning device of the present invention. In  FIG. 9 ,  201  is a monitoring camera,  202  is a self-contained sensor group,  203  is a motion velocity vector estimation processing device, and  205  is a motion velocity vector collation processing device. Furthermore,  601  is a wearing person identification information storage device,  604  is an identification information storage/display device, and  605  is an image analysis processing device. 
     The wearing person identification information storage device  601  is a device that stores and outputs identification information (information such as an individual ID and name) of a person that wears the self-contained sensor group. An output  603  of the identification information is identification information of the person wearing the self-contained sensor group  202 . The image analysis processing device  605  here analyzes an image from the monitoring camera  201 , estimates a motion velocity vector of a position of the feet of the human figure, and outputs its output data  211 . Simultaneously, the image analysis processing device  605  outputs output data  602  of region information in which the human figure is included. 
     The output data  602  of the region information is information indicative of a region of the human figure in the image. Moreover,  606  is output data  606  of a frame image of an image taken out from the output data  210  outputted from the monitoring camera  201 , and is inputted into the identification information storage/display device  604 . 
     The identification information storage/display device  604  receives, as input, the frame image  606 , the region information  602  of the human figure in the image, the identification information  603  of a person mounting the self-contained sensor group  202 , and a TRUE/FALSE signal  214  which is a result of a collation determination process of the two motion velocity vectors, which result is the output of the motion velocity vector collation processing device  205 . When the signal of the result of the collation determination process is the TRUE signal, the region information  602  of the frame image  606  of the monitoring camera is stored associated with the identification information  603  of the wearing person, and the identification information  603  is displayed on the image region indicated by the region information in the frame image. 
     As a result, in the moving body positioning device according to the present invention, when the motion velocity vector or motion vector of the human figure in the image of the monitoring camera is associated with the motion velocity vector or motion vector estimated based on the sensor data according to the self-contained sensor group, the human figure in the image of the monitoring camera may be associated with the identification information of the person wearing the self-contained sensor group, and display these information. 
     The moving body positioning device of the embodiment includes an identification information storage/display device  604  that stores and displays identification information identifying a moving body; when the motion velocity vector collation processing device  205  outputs a TRUE signal, the identification information storage/display device  604  stores and displays identification information of a moving body that wears the self-contained sensor  202  as information indicative of the moving body in the image of the monitoring camera  201 , and when the motion velocity vector collation processing device  205  outputs a FALSE signal, the identification information storage/display device  604  stores and displays identification information indicating that no self-contained sensor is worn, as the information indicative of the moving body in the image of the monitoring camera  201 . 
     Moreover, in the moving body positioning device according to the present invention, when the motion velocity vector or motion vector of the human figure in the image of the monitoring camera is associated with a motion velocity vector or motion vector estimated based on the sensor data according to the self-contained sensor group, it is possible to estimate with a certain probability that a person wearing the self-contained sensor group is present at a position on which a human figure is present, based on an image analysis of the monitoring camera. 
     In this case, when the image of the monitoring camera is collated with the output of the self-contained sensor, the position of the person wearing the self-contained sensor group is corrected to the position of the image analysis result. The position correction signal used at this time is outputted from the position correction signal output device  702 . 
       FIG. 10  is a block diagram illustrating a configuration of another embodiment of the moving body positioning device of the present invention. In  FIG. 10 ,  201  is a monitoring camera,  202  is a self-contained sensor group,  203  is a motion velocity vector estimation processing device,  204  is an image analysis processing device, and  205  is a motion velocity vector collation processing device. These components are configured similarly to the configuration of the embodiment of the moving body positioning device described with reference to  FIG. 2 . The  702  is a position correction signal output device. 
     The position correction signal output device  702  receives, as its input, positional information  701  of the feet of the human figure in the image, which is one output of the image analysis processing device  204 , and a signal (TRUE/FALSE signal)  214  of a collation result, which is an output of the motion velocity collation processing device  205 , and outputs the position correction signal  703 . The position correction signal  703  is used as a correction signal for an image analysis signal  701  outputted from the image analysis processing device  204 . The position correction signal output device  702 , when the motion velocity vector collation processing device  205  outputs a TRUE signal, outputs a positional coordinate of the moving body that is outputted from the image analysis processing device  204  as a signal for correcting as a position of the moving body on which the self-contained sensor group is worn. 
     INDUSTRIAL APPLICABILITY 
     A moving body positioning device of the present invention allows for correcting a position estimation result obtained by an internal observation device provided to a moving body with use of an external observation device such as a monitoring camera, thereby making it possible to measure, analyze, and estimate movement of a moving body more accurately. Accordingly, the moving body positioning device of the present invention is useful in an industrial manner. 
     REFERENCE SIGNS LIST 
       11  external observation device 
       12  internal observation device 
       21  external observation device 
       22  internal observation device 
       23  internal observation data processing device 
       24  external observation data processing device 
       25  collation processing device 
       101  monitoring camera 
       102  self-contained sensor group 
       201  monitoring camera 
       202  self-contained sensor group 
       203  motion velocity vector estimation processing device 
       204  image analysis processing device 
       205  motion velocity vector collation processing device 
       301  monitoring camera 
       302  self-contained sensor group 
       303  motion vector estimation processing device 
       304  image analysis processing device 
       305  motion vector collation processing device 
       505  walking parameter estimation processing device 
       601  wearing person identification information storage device 
       604  identification information storage/display device 
       605  image analysis processing device 
       702  position correction signal output device 
       3201  monitoring camera 
       3202  self-contained sensor group 
       3203  self-contained base movement kind processing device 
       3204  image analysis processing device 
       3205  movement kind collation processing device