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» Learning Mid-Level Features For Recognition
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CVPR
2008
IEEE
16 years 7 months ago
Hybrid body representation for integrated pose recognition, localization and segmentation
We propose a hybrid body representation that represents each typical pose by both template-like view information and part-based structural information. Specifically, each body par...
Cheng Chen, Guoliang Fan
159
Voted
ICARCV
2002
IEEE
126views Robotics» more  ICARCV 2002»
15 years 10 months ago
Gesture recognition using a probabilistic framework for pose matching
This paper presents an approach for view-based recognition of gestures. The approach is based on representing each gesture as a sequence of learned body poses. The gestures are re...
Ahmed M. Elgammal, Vhay Shet, Yaser Yacoob, Larry ...
ICCV
2009
IEEE
16 years 10 months ago
What is the Best Multi-Stage Architecture for Object Recognition?
In many recent object recognition systems, feature extraction stages are generally composed of a filter bank, a non-linear transformation, and some sort of feature pooling layer...
Kevin Jarrett, Koray Kavukcuoglu, Marc’Aurelio R...
ATAL
2007
Springer
15 years 11 months ago
Conditional random fields for activity recognition
Activity recognition is a key component for creating intelligent, multi-agent systems. Intrinsically, activity recognition is a temporal classification problem. In this paper, we...
Douglas L. Vail, Manuela M. Veloso, John D. Laffer...
CVPR
2011
IEEE
15 years 1 months ago
Hyper-graph Matching via Reweighted Random Walks
Establishing correspondences between two feature sets is a fundamental issue in computer vision, pattern recognition, and machine learning. This problem can be well formulated as g...
Jungmin Lee (Seoul National University), Minsu Cho...