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ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 9 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
CVPR
2003
IEEE
16 years 6 months ago
Nearest Neighbor Search for Relevance Feedback
We introduce the problem of repetitive nearest neighbor search in relevance feedback and propose an efficient search scheme for high dimensional feature spaces. Relevance feedback...
Jelena Tesic, B. S. Manjunath
CVPR
2004
IEEE
16 years 6 months ago
Wide Baseline Feature Matching Using the Cross-Epipolar Ordering Constraint
? Robust feature matching across different views of the same scene taken by two cameras with wide baseline and arbitrary rotation is still an open problem. Matching based on appear...
Xiaoye Lu, Roberto Manduchi
CVPR
2006
IEEE
16 years 6 months ago
Identifying Color in Motion in Video Sensors
Identifying or matching the surface color of a moving object in surveillance video is critical for achieving reliable object-tracking and searching. Traditional color models provi...
Gang Wu, Amir Rahimi, Edward Y. Chang, Kingshy Goh...
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ECCV
2008
Springer
16 years 6 months ago
Quick Shift and Kernel Methods for Mode Seeking
We show that the complexity of the recently introduced medoid-shift algorithm in clustering N points is O(N2 ), with a small constant, if the underlying distance is Euclidean. This...
Andrea Vedaldi, Stefano Soatto