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» Learning a Sparse Representation for Object Detection
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CVPR
2004
IEEE
15 years 11 months ago
Unsupervised Learning of Image Manifolds by Semidefinite Programming
Can we detect low dimensional structure in high dimensional data sets of images? In this paper, we propose an algorithm for unsupervised learning of image manifolds by semidefinit...
Kilian Q. Weinberger, Lawrence K. Saul

Publication
200views
13 years 5 months ago
Learning Tags from Unsegmented Videos of Multiple Human Actions
Providing methods to support semantic interaction with growing volumes of video data is an increasingly important challenge for data mining. To this end, there has been some succes...
Timothy Hospedales, Shaogang Gong, Tao Xiang
92
Voted
ECCV
2008
Springer
15 years 11 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
SIGSOFT
2009
ACM
15 years 4 months ago
Graph-based mining of multiple object usage patterns
The interplay of multiple objects in object-oriented programming often follows specific protocols, for example certain orders of method calls and/or control structure constraints...
Tung Thanh Nguyen, Hoan Anh Nguyen, Nam H. Pham, J...
82
Voted
AAAI
2004
14 years 11 months ago
Rapid Object Recognition from Discriminative Regions of Interest
Object recognition and detection represent a relevant component in cognitive computer vision systems, such as in robot vision, intelligent video surveillance systems, or multi-mod...
Gerald Fritz, Christin Seifert, Lucas Paletta, Hor...