Who's who in a sports video? An individual level sports video indexing system

Sports video analysis has attracted great attention in recent years. In the past decade, numerous sports video indexing approaches have been proposed at different semantic levels. In this paper, an individual level sports video indexing (ILSVI) scheme is proposed. The individual level refers to the indexing of a sports video on a player basis, i.e. to recognize each player in a multi-player game. Since the jersey number is always ''worn'' by a player as the player's identity in a game, it is feasible to recognize jersey numbers for individual level indexing in sports videos. To solve the jersey number recognition problem, a principal-axis based contour descriptor is proposed. Compared to the state-of-the-art approaches, the proposed descriptor can achieve higher recognition rate and only consume much less computation power. In addition, we developed an interactive system to realize the individual level sports video indexing (ILSVI). This interactive system includes a player detection and a jersey number detection sub-systems. The interactive system can help complete the individual level sports video indexing task. We shall use basketball game videos as the basis to develop real-world systems.