Combinational subsequence matching for human identification from general actions
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Identification and tracking of players in sport videos
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
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We are interested in the problem of automatic tracking and identification of players in broadcast sport videos shot with a moving camera from a medium distance. While there are many good tracking systems, there are fewer methods that can identify the tracked players. Player identification is challenging in such videos due to blurry facial features (due to fast camera motion and low-resolution) and rarely visible jersey numbers (which, when visible, are deformed due to player movements). We introduce a new system consisting of three components: a robust tracking system, a robust person identification system, and a conditional random field (CRF) model that can perform joint probabilistic inference about the player identities. The resulting system is able to achieve a player recognition accuracy up to 85% on unlabeled NBA basketball clips.