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ICMCS
2005
IEEE
218views Multimedia» more  ICMCS 2005»
13 years 10 months ago
A Mid-level Visual Concept Generation Framework for Sports Analysis
The development of mid-level concepts helps to bridge the gap between low-level feature and high-level semantics in video analysis. Most existing work combines the customized mid-...
Xiaofeng Tong, Lingyu Duan, Hanqing Lu, Changsheng...
SPIESR
2003
230views Database» more  SPIESR 2003»
13 years 6 months ago
Bridging the semantic gap in sports
One of the major challenges facing current media management systems and related applications is the so-called ‘‘semantic gap’’ between the rich meaning that a user desires...
Baoxin Li, James H. Errico, Hao Pan, M. Ibrahim Se...
CVPR
2007
IEEE
14 years 6 months ago
Segmental Hidden Markov Models for View-based Sport Video Analysis
We present a generative model approach to explore intrinsic semantic structures in sport videos, e.g., the camera view in American football games. We will invoke the concept of se...
Yi Ding, Guoliang Fan
TCSV
2008
153views more  TCSV 2008»
13 years 4 months ago
Broadcast Court-Net Sports Video Analysis Using Fast 3-D Camera Modeling
This paper addresses the automatic analysis of court-net sports video content. We extract information about the players, the playing-field in a bottom-up way until we reach scene-l...
Jungong Han, Dirk Farin, Peter H. N. de With
CVPR
2010
IEEE
13 years 5 months ago
Player Localization Using Multiple Static Cameras for Sports Visualization
We present a novel approach for robust localization of multiple people observed using multiple cameras. We use this location information to generate sports visualizations, which i...
Raffay Hamid, Ramkrishan Kumar, Matthias Grundmann...