Abstract:
A monitoring camera for generating a 3-dimensional (3D) image and a method of generating a 3D image using the same are provided. The monitoring camera includes: an imaging unit that is configured to laterally rotate and photograph an object to generate at least two images; and a controller that captures overlapping portions of images generated by the imaging unit, and generates a 3-dimensional (3D) image based on the overlapping portions.

Description:
CROSS-REFERENCE TO RELATED PATENT APPLICATION 
     This application claims priority from Korean Patent Application No. 10-2011-0027016, filed on Mar. 25, 2011, in the Korean Intellectual Property Office, the disclosure of which is incorporated herein in its entirety by reference. 
     BACKGROUND 
     1. Field 
     Methods and apparatuses consistent with the exemplary embodiments relate to a monitoring camera, and more particularly, to a monitoring camera for generating a 3-dimensional (3D) image and a method of generating a 3D image by using one monitoring camera. 
     2. Description of the Related Art 
     Monitoring cameras are widely used for security or crime prevention. Mostly, one monitoring camera is installed for surveillance. Thus, a 2-dimensional (2D) image captured by the monitoring camera is displayed on a monitor. The monitoring camera may monitor surroundings while performing a pan operation for rotating 360° in a horizontal direction, a tilt operation for rotating 90° in a vertical direction, and a zoom operation for expanding or reducing the size of an object. 
     In order to generate three-dimensional (3D) distance information, stereo vision using two cameras is required. In other words, when one monitoring camera is used, a 2D image is displayed on a screen since 3D information about a surveillance space and object cannot be generated despite that an actual surveillance space is 3D. Thus, the 2D image is discordant with a geometrical structure of the actual surveillance space when a function such as a privacy mask, or a pan, tilt, or zoom operation is performed. 
     This is because the monitoring camera generates 2D image information by using a plane charge-coupled device (CCD) sensor, and thus, 3D information is lost as image information in a 3D space is projected in 2D. 
     Examples of 3D information about an object include a distance between an object and a camera, a distance between an object and a background, and information about whether an object is spatially moving towards or away from a camera. 
     Since a monitoring camera in the related art cannot use distance information between an object and a background, i.e., 3D spatial information about an image being captured, a desired performance cannot be obtained while realizing a basic function, such as privacy mask. In other words, the related art monitoring camera monitors in 2D without recognizing a 3D space, such as a close object, a far object, an approaching object, a receding object, a close background, or a far background, and thus, distortedly recognizes a big object, a small object, an object increasing in size, an object decreasing in size, a big background, or a small background. 
     Such a spatial recognition may not be generated in a fixed monitoring camera instead of a pan-tilt-zoom (PTZ) camera. However, in the PTZ camera performing operations such as up-down-right-left movement, expansion, and reduction, the loss of 3D information in a surveillance area may cause problems. 
     SUMMARY 
     One or more exemplary embodiments provide a monitoring camera for generating a 3-dimensional (3D) image, and a method of generating a 3D image by using the monitoring camera. 
     According to an aspect of an exemplary embodiment, there is provided a monitoring camera for monitoring an object, the monitoring camera including: an imaging unit for photographing the object while laterally rotating; and a controller for capturing images overlapped with a time difference from among images generated by the imaging unit, and generating a 3-dimensional (3D) image by composing the overlapped images. 
     The controller may include: a panning driver for laterally rotating the imaging unit; an angle of view setter for setting an angle of view at which the imaging unit photographs the object; a crop image number setter for setting an overlap angle of neighboring images while generating a plurality of images by photographing the object at least twice with the set angle of view; a capturing unit for generating a plurality of crop images by capturing overlapped images of the neighboring images; and a composing unit for generating a 3D image of the object by composing the plurality of crop images into one continuous image. 
     The imaging unit may convert the captured images into an analog signal and transmit the analog signal to the controller. The overlap angle of the neighboring images may be changeable by a user. 
     The panning driver may rotate the imaging unit by 360°, and the composing unit may generate an omnidirectional 3D panoramic image. 
     Space information about the object may be obtained from the 3D image. The 3D image may be generated by the time difference of the neighboring images. 
     According to another aspect of an exemplary embodiment, there is provided a method of generating a 3-dimensional (3D) image by using a monitoring camera for generating a 3D image by photographing an object, the method including: setting an angle of view for photographing the object; photographing the object with the set angle of view while laterally rotating the monitoring camera; capturing an image including overlapped images generated via the photographing; and generating a 3D image by composing the captured image. 
     The method may further include, after the setting of the angle of view, setting an overlap angle of neighboring images while generating a plurality of images by photographing the object at least twice at the set angle of view. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The above and other aspects will become more apparent by describing in detail exemplary embodiments with reference to the attached drawings in which: 
         FIG. 1  is a diagram of an exterior of a monitoring camera according to an exemplary embodiment; 
         FIG. 2  is a block diagram of a monitoring camera according to an exemplary embodiment; 
         FIG. 3  is a block diagram of a controller of  FIG. 2 , according to an exemplary embodiment; 
         FIG. 4  is a diagram for describing an angle of view of a monitoring camera according to an exemplary embodiment; 
         FIG. 5  is a diagram for describing a photographing method of obtaining two images as a monitoring camera rotates according to an exemplary embodiment; 
         FIG. 6  illustrates two overlapped images generated by using the photographing method of  FIG. 5 ; 
         FIG. 7  illustrates one image divided into 4 crop images; 
         FIG. 8  illustrates a plurality of images obtained by reducing a rotation angle of a monitoring camera according to an exemplary embodiment; 
         FIGS. 9 through 12  are diagrams for describing a method of generating crop images by capturing overlapped images in  FIG. 8  according to an exemplary embodiment; 
         FIG. 13  illustrates an image generated by composing the crop images generated by using the method of  FIGS. 9 through 12  according to an exemplary embodiment; 
         FIG. 14  is a flowchart illustrating a method of generating a 3-dimensional (3D) image by using a monitoring camera, according to an exemplary embodiment; 
         FIG. 15  is a flowchart illustrating a method of detecting a distance between a monitoring camera and an object by using a detected 3D image, according to an exemplary embodiment; 
         FIGS. 16A and 16B  illustrate crop images generated by photographing a certain object; 
         FIG. 17A  illustrates an object image extracted by removing a background image from the crop image of  FIG. 16A ; 
         FIG. 17B  illustrates an object image extracted by removing a background image from the crop image of  FIG. 16B ; 
         FIG. 18A  is a graph showing a peak value of a correlation coefficient of the object image of  FIG. 17A ; and 
         FIG. 18B  is a graph showing a peak value of a correlation coefficient of the object image of  FIG. 17B . 
     
    
    
     DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS 
     Hereinafter, exemplary embodiments will be described more fully with reference to the accompanying drawings. In the drawings, like reference numerals denote like elements. 
       FIG. 1  is a diagram of an exterior of a monitoring camera  100  according to an exemplary embodiment and  FIG. 2  is a block diagram of the monitoring camera  100 . 
     Referring to  FIG. 1 , the monitoring camera  100  may be fixed to a particular space, such as a ceiling  111 , for safe photographing, and may perform a panning operation for laterally rotating 360°, a tilting operation for rotating up and down 90°, or a zooming operation for expanding or reducing the size of an object in an image captured by the monitoring camera  100 . 
     Referring to  FIG. 2 , the monitoring camera  100  includes an imaging unit  103 , a storage unit  104 , and a controller  105 . 
     The term “unit,” as used herein, means, but is not limited to, a software or hardware component, such as a Field Programmable Gate Array (FPGA) or an Application Specific Integrated Circuit (ASIC), which performs certain tasks. A unit may advantageously be configured to reside in the addressable storage medium and to execute on one or more processors. Thus, a unit may include, by way of example, components, such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables. The functionality provided for in the components and units may be combined into fewer components and units or further separated into additional components and units. In addition, the components and units may be implemented so as to execute one or more Central Processing Units (CPUs) in a device. 
     The imaging unit  103  photographs an object and transmits an image of the object to the controller  105 . The imaging unit  103  may include a lens system  101  including at least one lens and through which the image is penetrated, and an image pickup unit  102  including a plurality of image pickup devices for converting and outputting the image from the lens system  101  to an electric signal. 
     The lens system  101  may include a zoom lens (not shown) having a zoom function and a focus lens (not shown) having a focus adjusting function. The lens system  101  may also include an optical low pass filter (not shown) for removing optical noise. 
     The image pickup unit  102  may include a charge-coupled device (CCD) or a complementary metal oxide semiconductor (CMOS) to convert the image from the lens system  101  to an analog signal and transmit the analog signal to the controller  105 . 
     The controller  105  may convert analog image data output from the imaging unit  103  to digital data and process the digital data. The controller  105  may generate 3D image data by processing image data. The controller  105  controls a panning operation, a tilting operation, a zooming operation, and a photographing operation of the monitoring camera  100 . An image output from the controller  105  may be stored in a storage unit  104 , displayed on a monitor (not shown), or transmitted to another device via a network. The controller  105  may be provided as an individual unit that is separate from the monitoring camera  100 . The controller  105  will now be described in detail with reference to  FIG. 3 . 
       FIG. 3  is a block diagram of the controller  105  of  FIG. 2 , according to an exemplary embodiment. Referring to  FIG. 3 , the controller  105  includes a panning driver  311 , an angle of view setting unit  321 , a crop image number setting unit  331 , a capturing unit  341 , and a composing unit  351 . 
     The panning driver  311  laterally rotates the monitoring camera  100  up to 360°. In other words, the panning driver  311  may photograph an object while laterally and omnidirectionally rotating the monitoring camera  100 . A rotating speed and a rotating range of the monitoring camera  100  may be changed by a user. The rotating of the monitoring camera  100  means that the imaging unit  103  of the monitoring camera  100  rotates. In order for the panning driver  311  to pan the monitoring camera  100 , a pan motor (not shown) may be included in the monitoring camera  100 . The pan motor pans the monitoring camera  100  to the side. 
     The angle of view setting unit  321  sets an angle of view at which the monitoring camera  100  photographs the object. Referring to  FIG. 4 , the monitoring camera  100  photographs the object while laterally rotating 360°. An angle between a surface of the object and the monitoring camera  100  is called an angle of view A. The number of photographs taken to capture a scene during the 360° rotation of the monitoring camera is determined by the angle of view A. For example, when the angle of view A is 90°, the monitoring camera  100  may photograph 360° by photographing four times, and when the angle of view A is 60°, the monitoring camera  100  may photograph 360° by photographing 6 times. As such, a set value of the angle of view A of the monitoring camera  100  may be changed by a user. 
     The crop image number setting unit  331  sets an overlap angle of neighboring images when a plurality of images are generated by photographing the object at least twice by using the angle of view A set by the angle of view setting unit  321 . The number of crop images is determined by the overlap angle. A crop image is obtained by capturing the overlapped images of the neighboring images. For example, when the angle of view A of the monitoring camera  100  is 60° and the number of crop images is set to 4, the overlap angle is a value obtained by dividing the angle of view A by the number of crop images, i.e., 15°.  FIG. 7  illustrates an example of obtaining  4  crop images from one image. Here, the overlap angle of the neighboring images is set to ¼ of the angle of view A. The number of crop images may be changed by the user and may be set according to the characteristics of the object. 
     The capturing unit  341  generates a plurality of crop images by capturing the overlapped images of the neighboring images. In other words, the capturing unit  341  only captures overlapped images from among images captured as the monitoring camera  100  rotates 360°. Referring to  FIGS. 5 and 6 , when the monitoring camera  100  obtains two images V 1  and V 2  by photographing the object twice while rotating, overlapped images V( 1 , 2 ) of the two images V 1  and V 2  may be generated, and the capturing unit  341  captures the overlapped images V( 1 , 2 ). The overlapped images V( 1 , 2 ) have a time difference. That is, the monitoring camera  100  first obtains the image V 1  captured at an angle of view A 1  and then obtains the image V 2  captured at an angle of view A 2 . Accordingly, there is a time difference between the image V 1  captured at the angle of view A 1  and the image V 2  captured at the angle of view A 2 , and thus there is a time difference between the overlapped images V( 1 , 2 ). A crop image obtained by composing the overlapped images V( 1 , 2 ) having the time difference is a 3D image. 
     The number of crop images determines the size of the crop images. A plurality of crop images is obtained by images captured at one angle of view. For example, as shown in  FIG. 7 , there may be 4 crop images obtained by an image Vn captured at one angle of view. 
     Alternatively, as shown in  FIG. 8 , a plurality of first through seventh images V 1  through V 7  may be obtained when the object is photographed by the monitoring camera  100  by reducing a rotation angle. In other words,  FIG. 8  illustrates an example of obtaining  4  crop images from one image. 
     As shown in  FIG. 9 , a first crop image D 1  is obtained by capturing overlapped images V( 1 , 4 ) and V( 4 , 1 ) of the first and fourth images V 1  and V 4 . 
     As shown in  FIG. 10 , a second crop image D 2  is obtained by capturing overlapped images V( 2 , 5 ) and V( 5 , 2 ) of the second and fifth images V 2  and V 5 . 
     As shown in  FIG. 11 , a third crop image D 3  is obtained by capturing overlapped images V( 3 , 6 ) and V( 6 , 3 ) of the third and sixth images V 3  and V 6 . 
     As shown in  FIG. 12 , a fourth crop image D 4  is obtained by capturing overlapped images V( 4 , 7 ) and V( 7 , 4 ) of the fourth and seventh images V 4  and V 7 . 
     The composing unit  351  generates a 3D image shown in  FIG. 13  by sequentially composing the first through fourth crop images D 1  through D 4  captured by the capturing unit  341 . For example, the 3D image of  FIG. 13  is obtained by sequentially composing the first through fourth crop images D 1  through D 4  of  FIGS. 9 through 12 . 
     Then, when the crop images of the images obtained by photographing the object while the monitoring camera  100  rotates 360° are sequentially composed, an omnidirectional 3D panoramic image is generated. 
     Spatial information of the object may be extracted when such an omnidirectional 3D panoramic image is analyzed. 
       FIG. 14  is a flowchart illustrating a method of obtaining a 3D image by using the monitoring camera  100 , according to an exemplary embodiment. Referring to  FIG. 14 , the method includes five operations. The method of the monitoring camera  100  will now be described with reference to  FIGS. 1 through 13 . 
     In operation  1411 , the monitoring camera  100  sets an angle of view for photographing an object. 
     In operation  1421 , an overlap angle of neighboring images is set. 
     In operation  1431 , the monitoring camera  100  laterally rotates to photograph the object based on the set angle of view and overlap angle. 
     In operation  1441 , the monitoring camera  100  captures overlapped images of the generated images. 
     In operation  1451 , the monitoring camera  100  generates a 3D image by composing the captured overlapped images. 
     According to the method of the exemplary embodiment, one monitoring camera  100  may generate a 3D image. 
       FIG. 15  is a flowchart illustrating a method of detecting a distance between the monitoring camera  100  of  FIG. 4  and a certain object (not shown) by using a detected 3D image, according to an exemplary embodiment. Referring to  FIG. 15 , the method includes operations  1511  through  1561 . 
     In operation  1511 , two crop images V( 1 , 2 ) and V( 2 , 1 ) generated by photographing the certain object are prepared. The crop images V( 1 , 2 ) and V( 2 , 1 ) may obtained by using the method of  FIGS. 4 and 5 . Referring to  FIGS. 16A and 16B , the two crop images V( 1 , 2 ) and V( 2 , 1 ) generated by photographing the certain object include object images  1611  and  1612  and background images  1621  and  1622 , respectively. 
     In operation  1521 , the two object images  1611  and  1612  are extracted by removing the background images  1621  and  1622  from the two crop images V( 1 , 2 ) and V( 2 , 1 ).  FIG. 17A  illustrates the object image  1611  extracted by removing the background image  1621  from the crop image V( 1 , 2 ) of  FIG. 16A , and  FIG. 17B  illustrates the object image  1612  extracted by removing the background image  1622  from the crop image V( 2 , 1 ) of  FIG. 16B . 
     In operation  1531 , correlation coefficients c 1  and c 2  between object images are detected from the extracted object images  1611  and  1612 . Here, Equation 1 below may be used to detect the correlation coefficients c 1  and c 2 . 
     
       
         
           
             
               
                 
                   
                     
                       
                         
                           
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     In operation  1541 , peak values n 1  and n 2  of the correlation coefficients c 1  and c 2  are detected. Examples of the peak values n 1  and n 2  are shown in graphs of  FIGS. 18A and 18B . 
     In operation  1551 , an interval s between the object images  1611  and  1612  is calculated by using the peak values n 1  and n 2 . The interval s may be calculated by using Equation 2 below.
 
 s =abs( n 1 −n 2)  [Equation 2]
 
     Here, abs denotes an absolute value. 
     In operation  1561 , a distance between the monitoring camera  100  of  FIG. 4  and the certain object is calculated by applying the interval s between the object images  1611  and  1612 . A general method may be used to calculate the distance between the monitoring camera  100  of  FIG. 4  and the certain object by applying the interval s between the object images  1611  and  1612 . 
     As described above, the distance between the monitoring camera  100  of  FIG. 4  and the certain object may be calculated by using a 3D image generated according to an exemplary embodiment, and a mask may be set only on the certain object by using the distance. Accordingly, a privacy mask performance may be remarkably improved. 
     According to an exemplary embodiment, a 3D image is generated by capturing and composing two different images having a time difference while a single monitoring camera photographs an object. 
     Also, spatial information of the object can be extracted via the 3D image captured by using the single monitoring camera. 
     In addition, a mask can be set only on a certain object by using the extracted spatial information. Accordingly, a privacy mask performance can be remarkably improved. 
     While exemplary embodiments have been particularly shown and described, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present invention as defined by the following claims.