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PAMI
2011
13 years 2 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 ...
ICIP
2006
IEEE
14 years 9 months ago
A Hierarchical ASM/AAM Approach in a Stochastic Framework for Fully Automatic Tracking and Recognition
This paper deals with the fully automatic extraction of classifiable person features out of a video stream with challenging background. Basically the task can be split in two part...
Andre Störmer, Gerhard Rigoll, Sascha Schreib...
ICCV
2005
IEEE
14 years 9 months ago
A Generative/Discriminative Learning Algorithm for Image Classification
We have developed a two-phase generative / discriminative learning procedure for the recognition of classes of objects and concepts in outdoor scenes. Our method uses both multipl...
Yi Li, Linda G. Shapiro, Jeff A. Bilmes
CVPR
2010
IEEE
14 years 1 months ago
One-Shot Multi-Set Non-rigid Feature-Spatial Matching
We introduce a novel framework for nonrigid feature matching among multiple sets in a way that takes into consideration both the feature descriptor and the features spatial arra...
Marwan Torki and Ahmed Elgammal
CVPR
2008
IEEE
14 years 9 months ago
Granularity and elasticity adaptation in visual tracking
The observation models in tracking algorithms are critical to both tracking performance and applicable scenarios but are often simplified to focus on fixed level of certain target...
Ming Yang, Ying Wu