Balancing thread based navigation for targeted video search

Various query methods for video search exist. Because of the semantic gap each method has its limitations. We argue that for effective retrieval query methods need to be combined at retrieval time. However, switching query methods often involves a change in query and browsing interface, which puts a heavy burden on the user. In this paper, we propose a novel method for fast and effective search trough large video collections by embedding multiple query methods into a single browsing environment. To that end we introduced the notion of query threads, which contain a shot-based ranking of the video collection according to some feature-based similarity measure. On top of these threads we define several thread-based visualizations, ranging from fast targeted search to very broad exploratory search, with the Fork-Browser as the balance between fast search and video space exploration. We compare the effectiveness and efficiency of the ForkBrowser with the CrossBrowser on the TRECVID 2007 interactive search task. Results show that different query methods are needed for different types of search topics, and that the ForkBrowser requires significantly less user interactions to achieve the same result as the CrossBrowser. In addition, both browsers rank among the best interactive retrieval systems currently available.