Using Multiple-Hypothesis Disparity Maps and Image Velocity for 3-D Motion Estimation
International Journal of Computer Vision
Match Propogation for Image-Based Modeling and Rendering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Research and improvement on algorithm of image feature point matching
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Real-time stereo reconstruction in robotically assisted minimally invasive surgery
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
Accurate real-time neural disparity MAP estimation with FPGA
Pattern Recognition
A parallel version for the propagation algorithm
PaCT'05 Proceedings of the 8th international conference on Parallel Computing Technologies
Stereoscopic scene flow for robotic assisted minimally invasive surgery
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Image registration using BP-SIFT
Journal of Visual Communication and Image Representation
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A new robust dense matching algorithm is introduced in this paper. The algorithm starts from matching the most textured points, and then a match propagation algorithm is developed with the best first strategy to densify the matches. Next, the matching map is regularized by using the local geometric constraints encoded by planar affine applications and by using the global geometric constraint encoded by the fundamental matrix.Two most distinctive features are a match propagation strategy developed by analogy to region growing and a successive regularization by local and global geometric constraints. The algorithm is efficient, robust and can cope with wide disparity. The algorithm is demonstrated on many real image pairs and applications on image interpolation and creating novel views are presented.