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IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching Point Features with Ordered Geometric, Rigidity, and Disparity Constraints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Resolving Motion Correspondence for Densely Moving Points
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hopfield Neural Network Based Stereo Matching Algorithm
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Artificial Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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Gaussian and Laplacian of Gaussian weighting functions for robust feature based tracking
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Tracking feature points: dynamic programming algorithm
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Feature correspondence using probabilistic data association
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Occlusion and poor feature point detection are two of the main difficulties in the use of multiple frames for establishing correspondence of feature points. A formulation of the correspondence problem as an optimization problem is used to handle these difficulties. Modifications to an existing iterative optimization procedure for solving the formulation of the correspondence problem are discussed. Experimental results are presented to show the merits of the formulation.