Feature Point Correspondence in the Presence of Occlusion

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. >

[1]  Tomaso A. Poggio,et al.  On Edge Detection , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  S. Ullman The Interpretation of Visual Motion , 1979 .

[3]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[4]  Minoru Asada,et al.  Automatic Analysis of Moving Images , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Minoru Asada,et al.  Representation of three-dimensional motion in dynamic scenes , 1983, Comput. Vis. Graph. Image Process..

[6]  Peter J. Burt,et al.  Fast algorithms for estimating local image properties , 1982, Comput. Graph. Image Process..

[7]  R. F. Rashid,et al.  Towards a system for the interpretation of moving light displays , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Hans-Hellmut Nagel,et al.  Volumetric model and 3D trajectory of a moving car derived from monocular TV frame sequences of a street scene , 1981, Comput. Graph. Image Process..

[9]  Michael A. Arbib,et al.  Computing the optic flow: The MATCH algorithm and prediction , 1983, Comput. Vis. Graph. Image Process..

[10]  Andrew P. Witkin,et al.  Scale-Space Filtering , 1983, IJCAI.

[11]  J. Canny Finding Edges and Lines in Images , 1983 .

[12]  V. Ramachandran,et al.  The perception of apparent motion. , 1986, Scientific American.

[13]  John K. Tsotsos,et al.  Applying temporal constraints to the dynamic stereo problem , 1986, Comput. Vis. Graph. Image Process..

[14]  A. Rosenfeld,et al.  Edge and Curve Detection for Visual Scene Analysis , 1971, IEEE Transactions on Computers.

[15]  William B. Thompson,et al.  TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2009 .

[16]  Gérard G. Medioni,et al.  Fast Convolution with Laplacian-of-Gaussian Masks , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Ishwar K. Sethi,et al.  Finding Trajectories of Feature Points in a Monocular Image Sequence , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.