Robust descriptors for matching irregular regions automatically

Automatic feature matching, especially region matching, has made great progress in recent years, and a great deal of descriptor-based methods have been proposed. However, when constructing these descriptors for irregular regions, an extra step of fitting the irregular regions into fixed shape must be implemented in advance. The fitting step can cause great errors, and thus may result in poor matching. The main purpose of this paper is developing a strategy of constructing descriptors for irregular regions without any extra fitting steps. In this paper, two groups of descriptors are developed: one is the gradient-based descriptors and the other is the Harris-based descriptors. Experiments show that descriptors proposed in this paper can perform great and robust for irregular region matching on real images.

[1]  Hans P. Moravec.  Rover Visual Obstacle Avoidance , 1981, IJCAI.

[2]  Cordelia Schmid,et al.  Local Grayvalue Invariants for Image Retrieval , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Luc Van Gool,et al.  Affine/ Photometric Invariants for Planar Intensity Patterns , 1996, ECCV.

[4]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[5]  Cordelia Schmid,et al.  A Performance Evaluation of Local Descriptors , 2005, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Andrew Zisserman,et al.  Viewpoint invariant texture matching and wide baseline stereo , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[7]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[8]  Andrew Zisserman,et al.  Multi-view Matching for Unordered Image Sets, or "How Do I Organize My Holiday Snaps?" , 2002, ECCV.

[9]  Edward H. Adelson,et al.  The Design and Use of Steerable Filters , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Jiri Matas,et al.  Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..

[11]  Max A. Viergever,et al.  General Intensity Transformations and Second Order Invariants , 1992 .

[12]  Andrew E. Johnson,et al.  Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Rachid Deriche,et al.  A Robust Technique for Matching two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry , 1995, Artif. Intell..

[14]  Jitendra Malik,et al.  Shape matching and object recognition using shape contexts , 2010, 2010 3rd International Conference on Computer Science and Information Technology.