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» Sports Event Recognition Using Layered HMMS
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ICMCS
2007
IEEE
151views Multimedia» more  ICMCS 2007»
14 years 1 months ago
Exploring Contextual Information in a Layered Framework for Group Action Recognition
Contextual information is important for sequence modeling. Hidden Markov Models (HMMs) and extensions, which have been widely used for sequence modeling, make simplifying, often u...
Dong Zhang, Samy Bengio
ICASSP
2011
IEEE
12 years 11 months ago
Deep Belief Networks using discriminative features for phone recognition
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
MM
2004
ACM
244views Multimedia» more  MM 2004»
14 years 25 days ago
Automatic replay generation for soccer video broadcasting
While most current approaches for sports video analysis are based on broadcast video, in this paper, we present a novel approach for highlight detection and automatic replay gener...
Jinjun Wang, Changsheng Xu, Chng Eng Siong, Kongwa...
CVPR
2008
IEEE
14 years 9 months ago
Selective hidden random fields: Exploiting domain-specific saliency for event classification
Classifying an event captured in an image is useful for understanding the contents of the image. The captured event provides context to refine models for the presence and appearan...
Vidit Jain, Amit Singhal, Jiebo Luo
ICIP
2010
IEEE
13 years 5 months ago
Ball event recognition using hmm for automatic tennis annotation
A key element for video indexing and summarisation is the description of isolated events and actions. In the context of many sports the motion of the ball plays an essential role ...
Ibrahim Almajai, Josef Kittler, Teofilo de Campos,...