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» Unsupervised Learning of Invariant Features Using Video
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CVPR
2010
IEEE
14 years 5 months ago
A Hough Transform-Based Voting Framework for Action Recognition
We present a method to classify and localize human actions in video using a Hough transform voting framework. Random trees are trained to learn a mapping between densely-sampled f...
Angela Yao, Juergen Gall, Luc Van Gool
CVPR
2008
IEEE
14 years 10 months ago
A deformable local image descriptor
This paper presents a novel local image descriptor that is robust to general image deformations. A limitation with traditional image descriptors is that they use a single support ...
Hong Cheng, Zicheng Liu, Nanning Zheng, Jie Yang
TSD
2007
Springer
14 years 2 months ago
On the Relative Hardness of Clustering Corpora
Abstract. Clustering is often considered the most important unsupervised learning problem and several clustering algorithms have been proposed over the years. Many of these algorit...
David Pinto, Paolo Rosso
MM
2009
ACM
252views Multimedia» more  MM 2009»
14 years 3 months ago
Localizing volumetric motion for action recognition in realistic videos
This paper presents a novel motion localization approach for recognizing actions and events in real videos. Examples include StandUp and Kiss in Hollywood movies. The challenge ca...
Xiao Wu, Chong-Wah Ngo, Jintao Li, Yongdong Zhang
ECCV
2002
Springer
14 years 10 months ago
Learning to Parse Pictures of People
The detection of people is one of the foremost problems for indexing, browsing and retrieval of video. The main difficulty is the large appearance variations caused by action, clot...
Rémi Ronfard, Cordelia Schmid, Bill Triggs