An SVD approach to multi-camera-multi-target 3-D motion-shape analysis

An SVD approach to the so-called structure-from-motion problem was proposed by Tomasi and Kanade [1992]. The present paper extends the original motion-shape-estimation (MSE) to the multi-camera-multi-target case. The multi-target MSE problem is: given a sequence of 2D video images of multiple moving targets, the problem is to track the 3D motion of the targets and reconstruct their 3D shapes. This is further extended to multi-camera-multi-target MSE, with potential application to the 3D occlusion problem. After collection of feature points (FPs), which are sequentially tracked by a video system, the SVD may be applied to a measurement matrix formed by the FPs. The distribution of singular values would first reveal the information about the number of objects at hand. Then, using an algebraic-based subspace clustering method, the FPs may be mapped onto their corresponding objects. Thereafter, the motion and shape may be estimated from a matrix factorization