Theory of Stereo vision system

Transcription

1 Theory of Stereo vision system Introduction Stereo vision is a technique aimed at extracting depth information of a scene from two camera images. Difference in pixel position in two image produces the depth output. There are several other methods to measure depth of a scene, stereo vision is one among technique. Left image Right Image Depth Image

2 Intended Audience The document is intended for audience to help in understanding the concept of stereo vision system and estimating depth range of a system theoretically. Theory Below image depicts the working of stereo vision system. The above image depicts that two cameras capture a particular scene. The scene or image captured by the cameras are with a difference due to the distance the cameras are placed. The difference in pixel position of identical pixel in the images are called disparity. Disparity value will be high for nearer distance and will be low for far distance. Depth is inversely propositional to disparity. Since depth range depends on hardware parameters like focal length, baseline and pixel size also the equation is formulated as below. f=focal length b=baseline d=disparity value ps=pixel size D=Depth Focal length Focal length is the lens parameter of the camera system. It is the point where light rays converges to form a sharp image to the digital sensor. Focal length is represented in millimetre. Change in focal length of the cameras affects directly the depth range of stereo vision system, since stereo vision system is with two cameras both the cameras must be with identical focal length.

3 Baseline Baseline refers to the distance between left and right camera. Change in baseline directly affects the depth range of the stereo vision system. Baseline is represented in centimetre or millimetre. Pixel size Pixel size is the size of the individual pixel in an image sensor. Pixel size is represented in micrometre. Since stereo vision system uses two cameras the pixel size of the image sensor must be identical. As the pixel size decreases the depth range of the system increases.

4 Depth in m Depth in m Disparity value Disparity refers to difference in pixel position between two camera images. Assuming left image in stereo vision camera has a pixel at position (1, 30) and the same pixel is present at position (4, 30) in right image, the disparity value or difference is (4 1) =3. Disparity value is inversely proportional to depth as per the above formula. Disparity value d=3 Diagrammatic representation of Depth Range Above image depicts the depth range of a stereo vision system by applying disparity value from maximum to minimum. Graphical Representation of depth Range Depth Range of stereo vision system is represented graphically below and the depth at minimum distance alone is plotted in the second graph Graph for Depth vs Disparity Short Range Accuracy Graph Disparity Disparity

5 Short range in graph or disparity plane at minimum distance are the range where the depth is more accurate in stereo vision system. Disparity value is plotted in x axis and depth is plotted in y axis. Manual disparity calculation from stereo image pair The below scene is captured with a stereo vision system. In the above image, (303,232) is the pixel in the left image which is the edge of the bottle taken for validating the disparity value manually and in the same row searching for the identical pixel in the right image we could identify the pixel at (879,232) position. Since two images are concatenated the pixel value of second image is subtracted from the value 640(size of the image) i.e. ( =239). So the identical pixel position in the left and right image are in (303,232) and (239,232).The disparity between pixels of the bottle(object) present in the scene( =64). By applying the below value in Depth formula. Focal length =4.3 Baseline =60 mm Disparity value =64 Pixel size = =(4.3 *60)/(64*0.006) = mm =0.67 meter =67 centimetre. From the above result we could conclude that the bottle is kept at a distance of 67 centimetre. Conclusion The above article helps the user to refer when estimating the depth range of stereo vision system theoretically before designing or using a stereo vision system. Manual Disparity evaluation, Graphical and Diagrammatic representation of depth helps the reader to understand the concept more in detail. About Author Prashanth.R working as a senior engineer at e-con systems and working with the customers to choose the right camera for their end application scenarios. Prashanth holds Bachelors in Instrumentation Engineering worked in domains like IOT and robotics and can be reached at prashanth.r@e-consystems.com