Video-based image retrieval

Authors:
Linjun Yang;Yang Cai;Alan Hanjalic;Xian-Sheng Hua;Shipeng Li
Affiliations:
Microsoft Research Asia, Beijing, China;Zhejiang University, Hangzhou, Zhejiang, China;Delft University of Technology, Delft, Netherlands;Microsoft Bing, Bellevue, WA, USA;Microsoft Research Asia, Beijing, China
Venue:
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Year:
2011

Citing 4
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Abstract

Likely variations in the capture conditions (e.g. light, blur, scale, occlusion) and in the viewpoint between the query image and the images in the collection are the factors due to which image retrieval based on the Query-by-Example (QBE) principle is still not reliable enough. In this paper, we propose a novel QBE-based image retrieval system where users are allowed to submit a short video clip as a query to improve the retrieval reliability. Improvement is achieved by integrating the information about different viewpoints and conditions under which object and scene appearances can be captured across different video frames. Rich information extracted from a video can be exploited to generate a more complete query representation than in the case of a single-image query and to improve the relevance of the retrieved results. Our experimental results show that video-based image retrieval (VBIR) is significantly more reliable than the retrieval using a single image as a query.