Robotics and Computer Vision Lab

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저 자 Joonwoong Lee, In So Kweon
학 회 Pattern Recognition
논문일시(Year) 1998
논문일시(Month) 12
Vol. 31, No. 12, pp. 2017-2026

This paper proposes a segmentation algorithm by means of a probabilistic reasoning to segment moving vehicles in front of a moving vehicle in a road traffic scene. According to the perceptually known facts of a target, we extract image primitives and update a probabilistic expectation for the target to be in an image. Since a noise image produces unreliable features and degrades the detection and localization, selecting the image primitives, which are less sensitive to noise and represent the facts well, is important. The probabilistic reasoning overcomes this problem based on MAP (maximum a posteriori) probability that combines the prior and likelihood probabilities of image features using Bayes' rule.

List of Articles
39. Robust Model-based Scene Interpretation by Multilayered Context Information
Sungho Kim, In So Kweon
Computer Vision and Image Understanding (CVIU) 2007 / 03
38. Appearance-Cloning: Photo-Consistent Scene Recovery from Multi-View Images
Howon Kim, In So Kweon
International journal of computer vision (IJCV) 2006 / 02
37. Adaptive Support-Weight Approach for Correspondence Search
Kukjin Yoon, In So Kweon
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2006 / 04
36. Single-camera panoramic stereo system with single-viewpoint optics
Gijeong Jang, Sungho Kim, In So Kweon
Optics Letters 2006 / 01
35. 3D Target Recognition using Cooperative Feature Map Binding under Markov Chain Monte Carlo
Sungho Kim, In So Kweon
Pattern Recognition Letters 2006 / 05
34. An Effective 3D Target Recognition Imitating Robust Methods of Human Visual System
Sungho Kim, Gijeong Jang, In So Kweon
Pattern Analysis and Applications 2005 / 12
33. Geometric and algebraric constraints of projective concentric circles and their applications to camera calibration
Jun-sik Kim, Pirre Gurdjos, In So Kweon
IEEE Trans. on Pattern Analysis and Machine Intelligence 2005 / 04
32. Automatic model-based 3D object recognition by combining feature matching with tracking
Sungho Kim, In So Kweon
Machine Vision and Applications 2005 / 12
31. Combined model-based 3D object recognition
Sungho Kim, Gijeong Jang, Wangheon Lee, In So Kweon
International Journal of Pattern Recognition and Artificial Intelligence 2005 / 11
30. Voting-based Separation of Diffuse and Specular Pixels
Kukjin Yoon, In So Kweon
Electronics Letters 2004 / 09
29. Automatic edge detection using 3x3 ideal binary pixel patterns and fuzzy-based edge thresholding
Dongsu Kim, Wangheon Lee, In So Kweon
Pattern Recognition Letters 2004 / 10
28. Detecting cuts and dissolves through linear regression analysis
Seunghoon Han, In So Kweon
Electronics Letters 2003 / 10
27. Fast object recognition using dynamic programming from combination of salient line groups
Dongjoong Kang, Jongeun Ha, In So Kweon
Pattern Recognition 2003 / 01
26. COP : a new corner detector
Suncheol Bae, In So Kweon, Yoo Choong-Don
Pattern Recognition Letters 2002 / 09
25. Image-based visual servoing using position and angle of image features
Jaeseung Cho, In So Kweon
Electronics Letters 2001 / 07
24. Color indexing using chromatic invariant
Jiyeun Kim, Changyeong Kim, Seo Yang-Seck, In So Kweon
Pattern Recognition 2001 / 06
23. An edge-based algorithm for discontinuity adaptive color Image smoothing
Dongjoong Kang, In So Kweon
Pattern Recognition 2001 / 02
22. 3-D structure recovery and calibration under varying intrinsic parameters using known angles
Jongeun Ha, In So Kweon
Pattern Recognition 2001 / 02
21. Robust and direct estimation of 3-D motion and scene depth from stereo image sequences
Seongkee Park, In So Kweon
Pattern Recognition 2001 / 07
20. 3D object recognition using a new invariant relationship by single view
Kyoungsig Roh, In So Kweon
Pattern Recognition 2000 / 01
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