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» Learning Mid-Level Features For Recognition
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CVPR
2008
IEEE
14 years 11 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
ICARCV
2002
IEEE
126views Robotics» more  ICARCV 2002»
14 years 2 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
15 years 2 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
14 years 3 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
13 years 5 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...