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Published in:
2011 | OriginalPaper | Chapter
Feature-Assisted Dense Spatio-temporal Reconstruction from Binocular Sequences
Authors : Yihao Zhou, Yan Qiu Chen
Published in: Computer Vision – ACCV 2010
Publisher: Springer Berlin Heidelberg
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In this paper, a dynamic surface is represented by a triangle mesh with dense vertices whose 3D positions change over time. These time-varying positions are reconstructed by finding their corresponding projections in the images captured by two calibrated and synchronized video cameras. To achieve accurate dense correspondences across views and frames, we first match sparse feature points and rely on them to provide good initialization and strong constraints in optimizing dense correspondence. Spatio-temporal consistency is utilized in matching both features and image points. Three synergistic constraints, image similarity, epipolar geometry and motion clue, are jointly used to optimize stereo and temporal correspondences simultaneously. Tracking failure due to self-occlusion or large appearance change are automatically handled. Experimental results show that complex shape and motion of dynamic surfaces like fabrics and skin can be successfully reconstructed with the proposed method.