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» A New Bayesian Framework for Object Recognition
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CVPR
2009
IEEE
14 years 1 months ago
Learning multi-modal densities on Discriminative Temporal Interaction Manifold for group activity recognition
While video-based activity analysis and recognition has received much attention, existing body of work mostly deals with single object/person case. Coordinated multi-object activi...
Ruonan Li, Rama Chellappa, Shaohua Kevin Zhou
INTERSPEECH
2010
13 years 1 months ago
Boosted mixture learning of Gaussian mixture HMMs for speech recognition
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
Jun Du, Yu Hu, Hui Jiang
ICIP
2005
IEEE
14 years 8 months ago
Joint feature-spatial-measure space: a new approach to highly efficient probabilistic object tracking
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
Feng Chen, XiaoTong Yuan, ShuTang Yang
ICPR
2008
IEEE
14 years 1 months ago
Robust modeling and recognition of hand gestures with dynamic Bayesian network
In this paper, we propose a new gesture recognition model for a set of both one-hand and two-hand gestures based on the dynamic Bayesian network framework which makes it easy to r...
Heung-Il Suk, Bong-Kee Sin, Seong-Whan Lee
CVPR
2005
IEEE
14 years 9 months ago
Kernel-Based Bayesian Filtering for Object Tracking
Particle filtering provides a general framework for propagating probability density functions in non-linear and non-Gaussian systems. However, the algorithm is based on a Monte Ca...
Bohyung Han, Ying Zhu, Dorin Comaniciu, Larry S. D...