Query-based video event definition using rough set theory and video prototypes
Kimiaki Shirahama, Chieri Sugihara, Kuniaki Uehara · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010
Since a user wants to retrieve a great variety of events, it is impractical to index a video archive with predefined events. So, "query-based event definition" is essential to dynamically define events from example videos provided by the user. Especially, we address how to accurately cover a large variation of low-level features in an event. Specifically, due to arbitrary camera techniques and object movements, shots of the same event contain significantly different low-level features. That is, these shots are distributed in different subsets in the space of low-level features. So, we use "rough set theory" to extract each subset where example shots can be correctly classified by a simple combination of low-level features. Based on such subsets, we can retrieve various shots of the same event. But, this retrieval only for a wide coverage is not so accurate, where many irrelevant shots are ranked at top positions. Thus, we re-rank retrieved shots by finely matching them with example shots. With respect to this, since the original representation of a low-level feature is very high-dimensional, we use "video prototypes" which mask irrelevant dimensions to the above matching. Experimental results on TRECVID 2008 video archive show the possibility of our two-step method.