VisionGo: Towards video retrieval with joint exploration of human and computer
This paper introduces an effective interactive video retrieval system named VisionGo. It jointly explores human and computer to accomplish video retrieval with high effectiveness and efficiency. It assists the interactive video retrieval process in different aspects: (1) it maximizes the interaction efficiency between human and computer by providing a user interface that supports highly effective user annotation and an intuitive visualization of retrieval results; (2) it employs a multiple feedback technique that assists users in choosing proper method to enhance relevance feedback performance; and (3) it facilitates users to assess the retrieval results of motion-related queries by using motion-icons instead of static keyframes. Experimental results based on over 160h of news video shows demonstrate the effectiveness of the VisionGo system.
interactive video retrieval relevance feedback active learning