Experimental Study on Realtime Object Tracking Stystem

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(1) Fast and Reliable Extraction of Optical FlowAt every location, a flow vactor and its uncertainy measure are calculated from multiple constraint equations, which are obtained by convolving consecutive input images with a set of orientation-selective spatial filters.(2) Object Tracking Based on Optical FlowAn object is tracked by updating a rectangular window circumscribing the object region which has similar flow vectors. In multiple object tracking, a tracking window is assigned to each object. When two objects overlap, the foreground object is determined by comparing the flow in the overlapping region with that in each window. We also developed a method to track an object in a complicated background by integrating information over space and time.(3) Object Tracking Based on Optical Flow and EdgesEdges of an object are searched for around the object's motion boundary obtained from optical flow. The whole contour of the object is incrementally obtained by accumulating extracted edges. When two objects with similar motion overlap, the foreground object is determined by comparing the predicted contrours and the actual controur.(4) Object Tracking Based on Optical Flow and DisparityDisparity is calculated as optical flow between a pair of stereo images. An object region is extracted by Baysian inference using optical flow, disparity, and the predicted target location. The method can track an object even if the tracking with either flow vectors or disparities alone may fail.(5) Development of Realtime Tracking SystemAn experimental tracking system is composed of a DSP-based realtime image processor and an active stereo camera head. The image processor, which contains multiple DSP boards working in parallel, enables complex image processing in nearly a frame rate. We succeeded in realtime object tracking using the system.