Stereo Correspondence Through Feature Grouping and Maximal Cliques

The authors propose a method for solving the stereo correspondence problem. The method consists of extracting local image structures and matching similar such structures between two images. Linear edge segments are extracted from both the left and right images. Each segment is characterized by its position and orientation in the image as well as its relationships with the nearby segments. A relational graph is thus built from each image. For each segment in one image as set of potential assignments is represented as a set of nodes in a correspondence graph. Arcs in the graph represent compatible assignments established on the basis of segment relationships. Stereo matching becomes equivalent to searching for sets of mutually compatible nodes in this graph. Sets are found by looking for maximal cliques. The maximal clique best suited to represent a stereo correspondence is selected using a benefit function. Numerous results obtained with this method are shown. >

[1]  Robert E. Tarjan,et al.  Depth-First Search and Linear Graph Algorithms , 1972, SIAM J. Comput..

[2]  Harry G. Barrow,et al.  A Versatile Computer-Controlled Assembly System , 1973, IJCAI.

[3]  T. Pavlidis,et al.  PAVLIDIS AND HOROWITZ : PLANE CURVES sin , 2006 .

[4]  Harry G. Barrow,et al.  A Versatile System for Computer-Controlled Assembly , 1975, Artif. Intell..

[5]  T. O. Binford,et al.  Geometric Constraints In Stereo Vision , 1980, Optics & Photonics.

[6]  Robert C. Bolles,et al.  Locating Partially Visible Objects: The Local Feature Focus Method , 1980, AAAI.

[7]  Thomas O. Binford,et al.  Depth from Edge and Intensity Based Stereo , 1981, IJCAI.

[8]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[9]  Martin A. Fischler,et al.  Computational Stereo , 1982, CSUR.

[10]  R. Bolles,et al.  Recognizing and Locating Partially Visible Objects: The Local-Feature-Focus Method , 1982 .

[11]  Robert C. Bolles,et al.  3DPO: A Three- Dimensional Part Orientation System , 1986, IJCAI.

[12]  T. Poggio,et al.  A generalized ordering constraint for stereo correspondence , 1984 .

[13]  J P Frisby,et al.  PMF: A Stereo Correspondence Algorithm Using a Disparity Gradient Limit , 1985, Perception.

[14]  W. Eric L. Grimson,et al.  Computational Experiments with a Feature Based Stereo Algorithm , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Ramakant Nevatia,et al.  Segment-based stereo matching , 1985, Comput. Vis. Graph. Image Process..

[16]  Takeo Kanade,et al.  Stereo by Intra- and Inter-Scanline Search Using Dynamic Programming , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Takeo Kanade,et al.  Incremental Reconstruction of 3D Scenes from Multiple, Complex Images , 1986, Artif. Intell..

[18]  Kim L. Boyer,et al.  Structural Stereopsis for 3-D Vision , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Thomas Skordas.  Mise en correspondance et reconstruction stéréo utilisant une description structurelle des images. (Stereo corresponding and reconstruction by image Structural description) , 1988 .