ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Motion and Episode Models for (Simulated) Football Games: Acquisition, Representation, and Use
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Computerized Real-Time Analysis of Football Games
IEEE Pervasive Computing
Camera-based observation of football games for analyzing multi-agent activities
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
ISM '06 Proceedings of the Eighth IEEE International Symposium on Multimedia
Automatic player detection, labeling and tracking in broadcast soccer video
Pattern Recognition Letters
Automatic soccer players tracking in goal scenes by camera motion elimination
Image and Vision Computing
Tracking the soccer ball using multiple fixed cameras
Computer Vision and Image Understanding
Visually tracking football games based on TV broadcasts
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Tracking soccer players aiming their kinematical motion analysis
Computer Vision and Image Understanding
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In sports events shown on TV or on the Internet, having the names and uniform numbers of the players displayed beside the players on the screen helps viewers to identify the players. Conventional methods of annotating and tracking objects utilize image recognition techniques with high-resolution images, so players captured on camera from a long distance are too small for accurate recognition. In response to this problem, we propose a method for identifying and tracking moving objects with a combination of wearable acceleration sensors and image recognition techniques. In our method, the method recognizes moving objects by matching the context picked up by the wearable sensors with the context inferred during the image processing. Evaluation results demonstrated the effectiveness of the proposed method.