Genre categorization of amateur sports videos in the wild

Various sports video genre categorization methods are proposed recently, mainly focusing on professional sports videos captured for TV broadcasting. This paper aims to categorize sports videos in the wild, captured using mobile phones by people watching a game or practicing a sport. Thus, no assumption is made about video production practices or existence of field lining and equipment. Motivated by distinctiveness of motions in sports activities, we propose a novel motion trajectory descriptor to effectively and efficiently represent a video. Furthermore, temporal analysis of local descriptors is proposed to integrate the categorization decision over time. Experiments on a newly collected dataset of amateur sports videos in the wild demonstrate that our trajectory descriptor is superior for sports videos categorization and temporal analysis improves the categorization accuracy further.