Semantic context transfer across heterogeneous sources for domain adaptive video search

Automatic video search based on semantic concept detectors has recently received significant attention. Since the number of available detectors is much smaller than the size of human vocabulary, one major challenge is to select appropriate detectors to response user queries. In this paper, we propose a novel approach that leverages heterogeneous knowledge sources for domain adaptive video search. First, instead of utilizing WordNet as most existing works, we exploit the context information associated with Flickr images to estimate query-detector similarity. The resulting measurement, named Flickr context similarity (FCS), reflects the co-occurrence statistics of words in image context rather than textual corpus. Starting from an initial detector set determined by FCS, our approach novelly transfers semantic context learned from test data domain to adaptively refine the query-detector similarity. The semantic context transfer process provides an effective means to cope with the dom...

• Type: Conference
• Year: 2009
• Where: MM
• Authors: Yu-Gang Jiang, Chong-Wah Ngo, Shih-Fu Chang
• Keywords: MM 2009, Multimedia, Semantic Context, Semantic Context Transfer, Video Search