Abstract
A novel active-contour method is presented and applied to pose refinement and tracking. The main innovation is that no ”features” are detected at any stage: contours are simply assumed to remove statistical dependencies between pixels on opposite sides of the contour. This assumption, together with a simple model of shape variability of the geometric models, leads to the application of an EM method for maximizing the likelihood of pose parameters. In addition, a dynamical model of the system leads to the application of a Kalman filter. The method is demonstrated by tracking motor vehicles with 3-D models.
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Pece, A.E.C., Worrall, A.D. (2002). Tracking with the EM Contour Algorithm. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds) Computer Vision — ECCV 2002. ECCV 2002. Lecture Notes in Computer Science, vol 2350. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47969-4_1
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DOI: https://doi.org/10.1007/3-540-47969-4_1
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