iARM - an interactive video retrieval system

This work presents the iARM system for content-based video retrieval in an interactive framework. This system explores a new model-based video indexing technique to improve the effectiveness of relevance feedback and make interactive video retrieval a user-friendly environment. The system emphasizes the accuracy in modeling spatio-temporal information in a video clip, so that relevance feedback analysis needs only a few cycles and a few training samples, which greatly reduce the search time for video transmissions over the network. We investigate the resilience of the system, and apply the interactive content-based retrieval method to an automatically indexed database of 20 hours of video.