Automatic detection of 'Goal' segments in basketball videos
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Replay Detection in Broadcasting Sports Video
ICIG '04 Proceedings of the Third International Conference on Image and Graphics
Detection of slow-motion replay segments in sports video for highlights generation
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
TV program segmentation using multi-modal information fusion
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Event detection models using 2d-BN and CRFs
MMM'07 Proceedings of the 13th International conference on Multimedia Modeling - Volume Part II
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Replays are key cues for events detection in sport videos since they are the immediate consequence of highlights or important events happened in sports. In many sports videos, replays are usually sandwiched with two identical logo transitions, prompt the beginning and end of a replay. A logo transition is a kind of special digital video effects, usually contains 12-35 consecutive frames, describe a flying or variable object. In this paper, a novel automatic logo detection approach is proposed. It contains two main stages: a logo transition template is automatically learned by dynamic programming and unsupervised clustering, a key frame is also extracted; then the extracted key frame and the learned logo template are used jointly to detect logos in sports videos. The optical flow features are used to depict the motion characteristics of the logo transitions. Experiments on different types of sports videos show that the proposed approach can reliably detect logos in sports videos efficiently.