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» Representation and Recognition of Complex Human Motion
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TIP
2008
165views more  TIP 2008»
13 years 7 months ago
Activity Modeling Using Event Probability Sequences
Changes in motion properties of trajectories provide useful cues for modeling and recognizing human activities. We associate an event with significant changes that are localized in...
Naresh P. Cuntoor, B. Yegnanarayana, Rama Chellapp...
GECCO
2009
Springer
258views Optimization» more  GECCO 2009»
14 years 5 days ago
Evolutionary learning of local descriptor operators for object recognition
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Cynthia B. Pérez, Gustavo Olague
ICCV
2007
IEEE
14 years 9 months ago
Real-time Body Tracking Using a Gaussian Process Latent Variable Model
In this paper, we present a tracking framework for capturing articulated human motions in real-time, without the need for attaching markers onto the subject's body. This is a...
Shaobo Hou, Aphrodite Galata, Fabrice Caillette, N...
ICCV
2009
IEEE
13 years 5 months ago
Fast realistic multi-action recognition using mined dense spatio-temporal features
Within the field of action recognition, features and descriptors are often engineered to be sparse and invariant to transformation. While sparsity makes the problem tractable, it ...
Andrew Gilbert, John Illingworth, Richard Bowden
CVIU
2006
158views more  CVIU 2006»
13 years 7 months ago
Sequential mean field variational analysis of structured deformable shapes
A novel approach is proposed to analyzing and tracking the motion of structured deformable shapes, which consist of multiple correlated deformable subparts. Since this problem is ...
Gang Hua, Ying Wu