PDF-Local feature detectors and descriptors

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CS 6350

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Local feature detectors and descriptors: Transcript

CS 6350. Bart Adams. Stanford University / KU Leuven. Richard Keiser. LiberoVision. Inc. / ETH Zurich. Mark . Pauly. ETH Zurich. Leonidas. J. . Guibas. Stanford University. 그래픽스 연구실. 하래주. Image from http://graphics.cs.cmu.edu/courses/15-463/2010_fall/. Robust feature-based alignment. So far, we’ve assumed that we are given a set of “ground-truth” correspondences between the two images we want to align. Matthew Brown. University of British Columbia. (prev.) Microsoft Research. [ Collaborators: . †. Simon Winder, *Gang . Hua. , . †. Rick . Szeliski. . †. =MS Research, *=MS Live Labs]. Applications @MSFT. vision. Applications and Algorithms in CV. Tutorial . 9:. Descriptors. Visual Descriptors. Motivation::. Scene Classification. I. ntroduction. How to differentiate between scenes?. Applications and Algorithms in CV. Eric Brenner. Paul Carpenter. Daniel Ehrenberg. Aaron McCarty. Travis Raines. Advised by Jeff . Ondich. Defining the Problem. What is optical character recognition (OCR)?. Input: an image of some text. Shulin. (Lynn) . Yang University . of . Washington. Mei . Chen . Intel Labs . Pittsburgh. Dean . Pomerleau. . Robotics . Institute. Rahul . Sukthankar. . 3 types of descriptors. :. SIFT / PCA-SIFT . (. Ke. , . Sukthankar. ). GLOH . (. Mikolajczyk. , . Schmid. ). DAISY . (. Tola. , et al, Winder, et al). Comparison of descriptors . (. Mikolajczyk. Taylor J. Meek. October 22, 2009. Evidence and Consequences of Feature Detection in The Visual Pattern Recognition of Reading by . Taylor J. Meek. is licensed under a . Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License. CS5670: Computer Vision. Noah Snavely. Reading. Szeliski: 4.1. Announcements. Project 1 Artifacts due tomorrow, Friday 2/17, at 11:59pm. Project 2 will be released next week. In-class quiz at the beginning of class Thursday. Samantha Horvath. Learning Based Methods in Vision. 2/14/2012. Introduction. Computer vision makes use of many “hand-crafted” descriptors.. These descriptors share many common components. This paper presents a modular framework for designing and optimizing new feature descriptors . Oscar . Danielsson. (osda02@csc.kth.se). Stefan . Carlsson. (. stefanc@csc.kth.se. ). Josephine Sullivan (. sullivan@csc.kth.se. ). DICTA08. The Problem. Object categories are often modeled by collections (bag-of-features) or constellations (pictorial structures) of local features . Second-Order Pooling. João Carreira. 1,2. , Rui Caseiro. 1. , Jorge Batista. 1. , Cristian Sminchisescu. 2. 1. . Institute of Systems and Robotics. ,. . University of Coimbra. 2. . Faculty of Mathematics and Natural . Kenton McHenry, Ph.D.. Research Scientist. Raster Images. 0.92. 0.93. 0.94. 0.97. 0.62. 0.37. 0.85. 0.97. 0.93. 0.92. 0.99. 0.95. 0.89. 0.82. 0.89. 0.56. 0.31. 0.75. 0.92. 0.81. 0.95. 0.91. 0.89. 0.72. Basic correspondence. Image patch as descriptor, NCC as similarity. Invariant to?. Photometric transformations?. Translation?. Rotation?. Scaling?. Find dominant orientation of the image patch. This is given by .

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