Visual Object Tracking Based on a Multi-Viewpoint 3D Gradient Method

Publisher Summary A method for 3D motion tracking without feature extraction is necessary for monitoring human action in a normal civil-life scene. To create a fast and robust object tracking method, this chapter proposes a model-based method using intensity images taken with a multiple viewpoint camera connected to a PC cluster system. First, the whole 3D shape and reflectance model of the object are prepared using several rangefinders. Each rangefinder is constructed with a camera, projector, and PC, and all PCs are connected via network to each other. For tracking the object, several CG images with varied object pose and position are generated in each PC using the object model and then compared to the input intensity image in parallel. The result of the comparison is transferred to a master PC, and the pose and position of the object are estimated by minimizing the residual of the CG and input images. The chapter makes a special CG generator, which is a precise simulator of the real camera to generate a CG image identical to the input image.

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