Experiments in Using Visual and Textual Clues for Image Hunting on the Web
In this paper we describe our experiences with Diogenes, a web-based search agent for finding person images. Diogenes1 implements different ways of combining visual and textual information for identifying person images. The sources of visual information are a face detection and a face recognition module. The textual information is obtained by analyzing the HTML structure and full text of web pages. Four different ways of combining these pieces of information are evaluated experimentally: (1) Face detection followed by text/HTML analysis, (2) face detection followed by face recognition, a linear combination of (1) and (2) and finally, a Dempster-Shafer combination of (1) and (2). We also compare the performance of Diogenes to those of research prototype and commercial image search engines. We report the results of a set of experimental retrievals for 20 persons examining over 30,000 URLs. In these retrievals Diogenes had the best average precision among the search engines evaluated including WebSEEk, AltaVista, Lycos and Ditto.
KeywordsFace Recognition Facial Image Image Retrieval Average Precision Face Detection
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