Content-based image retrieval (CBIR) has become one of the most active research areas in the past few years. Many visual feature representations have been explored and many systems built. While these research efforts establish the basis of CBIR, the usefulness of the proposed approaches is limited. Specifically, these efforts have relatively ignored two distinct characteristics of CBIR systems: (1) the gap between high level concepts and low level features; (2) subjectivity of human perception of visual content. This paper proposes a relevance feedback based interactive retrieval approach, which effectively takes into account the above two characteristics in CBIR. During the retrieval process, the user's high level query and perception subjectivity are captured by dynamically updated weights based on the user's relevance feedback. The experimental results show that the proposed approach greatly reduces the user's effort of composing a query and captures the user's information need more precisely.
Conference Committee Involvement (9)
Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications 2015
10 February 2015 | San Francisco, California, United States
Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications 2014
3 February 2014 | San Francisco, California, United States
Multimedia Content Access: Algorithms and Systems VII
4 February 2013 | Burlingame, California, United States
Internet Imaging VII
18 January 2006 | San Jose, California, United States
Multimedia Systems and Applications VIII
24 October 2005 | Boston, MA, United States
Internet Imaging VI
19 January 2005 | San Jose, California, United States
Storage and Retrieval Methods and Applications for Multimedia 2005
18 January 2005 | San Jose, California, United States
Internet Multimedia Management Systems V
27 October 2004 | Philadelphia, Pennsylvania, United States
Internet Multimedia Management Systems IV
10 September 2003 | Orlando, Florida, United States
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