Motion detection and tracking using deformable templates

We propose an object-based framework for detection and tracking of moving objects in a sequence of images. Two key ingredients of the approach are appropriate object models based on Grenander's (see General Pattern Theory, 1993) deformable templates and spatio-temporal data models. Detection and tracking problems are formulated as optimization problems. Detection employs a Metropolis-type procedure starting from a random initial configuration, while tracking involves a deterministic nonlinear Gauss-Seidel algorithm. We present experimental results with real data on a highway traffic sequence.<>