Applying temporal constraints to the dynamic stereo problem
Computer Vision, Graphics, and Image Processing - Lectures notes in computer science, Vol. 201 (G. Goos and J. Hartmanis, Eds.)
Binocular Image Flows: Steps Toward Stereo-Motion Fusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Correspondenceless Stereo and Motion: Planar Surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Graduated Assignment Algorithm for Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo-Motion with Stereo and Motion in Complement
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo and motion correspondences using nonlinear optimization method
Computer Vision and Image Understanding
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New similarity function S3 and energy function E3 of multiple feature tracking are formulated for especially rapidly changing motion in this paper. Stereo and motion cues are tightly coupled in the similarity function S3. Thus this property makes the similarity function S3 control repetition ambiguity almost completely. Seven assignment matrices to maximize the seventh dimensional nonlinear energy function E3 is obtained for applying the similar algorithm which we previously proposed in [3]. Even though proposed measurements suggest perfect solution for feature tracking, it needs high computational processing time.