el-based tracking of humans in action:

We present a vision system for the 3-0 modelbased tracking of unconstrained human movement. Using image sequences acquzred szmultaneously from multiple views, we recover the 3-0 body pose at each time instant without the use of markers. The poserecovery problem is formulated as a search problem and entails finding the pose parameters of a graphical human model whose synthesized appearance is most similar to the actual appearance of the real human in the multi-view images. The models used for this purpose are acquiredfrom the images. We use a decomposition approach and a best-first technique to search through the high dimensional pose parameter space. A robust variant of chamfer matching is used as a fast similarity measure between synthesized and real edge images. We present initial tracking results from a large new Humans-In-Action (HIA) database containing more than 2500 frames tn each of four orthogonal vzews. They contain subjects involved in a variety of activities, of various degrees of complexity, rangzng from the more simple one-person hand waving to the chailenging two-person close interaction in the Argentine Tango.