Computer Vision and Image Understanding
Tracking of multiple objects using optical flow based multiscale elastic matching
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
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This paper describes a novel method for performing spatially coherent motion estimation by integrating region and boundary information. The method begins with a layered, parametric flow model. Since the resulting flow estimates are typically sparse, we use the computed motion in a novel way to compare intensity values between images, thereby providing improved spatial coherence of a moving region. This dense set of intensity constraints is then used to initialize an active contour, which is influenced by both motion and intensity data to track the object's boundary. The active contour, in turn, provides additional spatial coherence by identifying motion constraints within the object boundary and using them exclusively in subsequent motion estimation for that object. The active contour is therefore automatically initialized once and, in subsequent frames, is warped forward based on the motion model. The spatial coherence constraints provided by both the motion and the boundary information act together to overcome their individual limitations. Furthermore, the approach is general, and makes no assumptions about a static background and/or a static camera. We apply the method to image sequences in which both the object and the background are moving.