Relevance Feedback Techniques in Interactive Content-Based Image Retrieval

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 e orts establish the basis of CBIR, the usefulness of the proposed approaches is limited. Speci cally, these e orts 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 e ectively 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 e ort of composing a query and captures the user's inform...

• Type: Conference
• Year: 1998
• Where: SPIESR
• Authors: Yong Rui, Thomas S. Huang, Sharad Mehrotra
• Keywords: CBIR Systems, Content-based Image Retrieval, Relevance Feedback, SPIESR 1998, SPIESR 2001