Joint tracking of features and edges

Sparse features have traditionally been tracked from frame to frame independently of one another. We propose a framework in which features are tracked jointly. Combining ideas from Lucas-Kanade and Horn-Schunck, the estimated motion of a feature is influenced by the estimated motion of neighboring features. The approach also handles the problem of tracking edges in a unified way by estimating motion perpendicular to the edge, using the motion of neighboring features to resolve the aperture problem. Results are shown on several image sequences to demonstrate the improved results obtained by the approach. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Anchorage, Alaska, June 2008 c 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in ...

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Stanley T. Birchfield, Shrinivas J. Pundlik
• Keywords: Aperture Problem, Computer Vision, CVPR 2008, IEEE Conference, Sparse Features