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PAMI
2011
12 years 12 months ago
Learning a Family of Detectors via Multiplicative Kernels
—Object detection is challenging when the object class exhibits large within-class variations. In this work, we show that foreground-background classification (detection) and wit...
Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan ...
MIR
2006
ACM
141views Multimedia» more  MIR 2006»
13 years 11 months ago
Mining temporal patterns of movement for video content classification
Scalable approaches to video content classification are limited by an inability to automatically generate representations of events ode abstract temporal structure. This paper pre...
Michael Fleischman, Philip DeCamp, Deb Roy
CVPR
2009
IEEE
1413views Computer Vision» more  CVPR 2009»
15 years 1 days ago
Learning Semantic Scene Models by Object Classification and Trajectory Clustering
The visual surveillance task is to monitor the activity of objects in a scene. In far-field settings (i.e., wide outdoor areas), the majority of visible activities are objects movi...
Hanqing Lu, Stan Z. Li, Tianzhu Zhang
ICCV
2003
IEEE
14 years 6 months ago
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
CVPR
2000
IEEE
14 years 7 months ago
Impact of Dynamic Model Learning on Classification of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and analysis of figure motion has employed eith...
Vladimir Pavlovic, James M. Rehg