A space-sweep approach to true multi-image matching

The problem of determining feature correspondences across multiple views is considered. The term "true multi-image" matching is introduced to describe techniques that make full and efficient use of the geometric relationships between multiple images and the scene. A true multi-image technique must generalize to any number of images, be of linear algorithmic complexity in the number of images, and use all the images in an equal manner. A new space-sweep approach to true multi-image matching is presented that simultaneously determines 2D feature correspondences and the 3D positions of feature points in the scene. The method is illustrated on a seven-image matching example from the aerial image domain.

[1]  R. F.,et al.  Mathematical Statistics , 1944, Nature.

[2]  Roger Y. Tsai Multiframe Image Point Matching and 3-D Surface Reconstruction , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  J. Canny A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Y. J. Tejwani,et al.  Robot vision , 1989, IEEE International Symposium on Circuits and Systems,.

[5]  F. Frances Yao,et al.  Computational Geometry , 1991, Handbook of Theoretical Computer Science, Volume A: Algorithms and Complexity.

[6]  Donald J. Gerson RADIUS: the government viewpoint , 1992, Other Conferences.

[7]  Christian Heipke,et al.  Global image matching and surface reconstruction in object space using aerial images , 1993, Defense, Security, and Sensing.

[8]  Charles K. Toth,et al.  Use of object space matching for feature extraction in multiple aerial images , 1993, Defense, Security, and Sensing.

[9]  Jon A. Webb Implementation and performance of fast parallel multi-baseline stereo vision , 1993, 1993 Computer Architectures for Machine Perception.

[10]  Takeo Kanade,et al.  A Multiple-Baseline Stereo , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  P. Anandan,et al.  Direct recovery of shape from multiple views: a parallax based approach , 1994, Proceedings of 12th International Conference on Pattern Recognition.

[12]  Rakesh Kumar,et al.  Shape Recovery from Multiple Views: A Parallax Based Approach , 1994 .

[13]  Amnon Shashua,et al.  Trilinearity in Visual Recognition by Alignment , 1994, ECCV.

[14]  Bill Triggs,et al.  Matching constraints and the joint image , 1995, Proceedings of IEEE International Conference on Computer Vision.

[15]  Steven M. Seitz,et al.  Complete scene structure from four point correspondences , 1995, Proceedings of IEEE International Conference on Computer Vision.

[16]  Takeo Kanade,et al.  Development of a video-rate stereo machine , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[17]  Ingemar J. Cox,et al.  A multiple-baseline stereo for precise human face acquisition , 1997, Pattern Recognit. Lett..