Object tracking via uncertainty minimization
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Contour tracking using modified canny edge maps with level-of-detail
CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
Object tracking and elimination using level-of-detail canny edge maps
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
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We propose a new method for contour tracking in video. The inverted distance transform of the edge map is used as an edge indicator function for contour detection. Using the concept of topographical distance, the watershed segmentation can be formulated as a minimization. This new viewpoint gives a way to combine the results of the watershed algorithm on different surfaces. In particular, our algorithm determines the contour as a combination of the current edge map and the contour, predicted from the tracking result in the previous frame. We also show that the problem of background clutter can be relaxed by taking the object motion into account. The compensation with object motion allows to detect and remove spurious edges in background. The experimental results confirm the expected advantages of the proposed method over the existing approaches.