A New Approach to Tracking 3D Objects in 2D Image Sequences

Book One

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 12

Perception

We present a new technique for tracking 3D objects from 2D image sequences through the integration of qualitative and quantitative techniques. The deformable models are initialized based on a previously developed part-based qualitative shape segmentation system. Using a physics-based quantitative approach, objects are subsequently tracked without feature correspondence based on generalized forces computed from the stereo images. The automatic prediction of possible edge occlusion and disocclusion is performed using an extended Kalman filter. To cope with possible occlusion caused by a previously undetected object, we monitor the magnitude and direction of the computed image forces exerted on the models. Abrupt changes to these forces trigger scene re-segmentation and model re-initialization through the qualitative shape segmentation system. Tracking is subsequently continued using only local image forces. We demonstrate our technique in experiments involving image sequences from complex motions of 3D objects.