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Author Mei, Tao ♦ Rui, Yong ♦ Li, Shipeng ♦ Tian, Qi
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2014
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Multimedia information retrieval ♦ Search re-ranking ♦ Survey ♦ Visual search
Abstract The explosive growth and widespread accessibility of community-contributed media content on the Internet have led to a surge of research activity in multimedia search. Approaches that apply text search techniques for multimedia search have achieved limited success as they entirely ignore visual content as a ranking signal. Multimedia search reranking, which reorders visual documents based on multimodal cues to improve initial text-only searches, has received increasing attention in recent years. Such a problem is challenging because the initial search results often have a great deal of noise. Discovering knowledge or visual patterns from such a noisy ranked list to guide the reranking process is difficult. Numerous techniques have been developed for visual search re-ranking. The purpose of this paper is to categorize and evaluate these algorithms. We also discuss relevant issues such as data collection, evaluation metrics, and benchmarking. We conclude with several promising directions for future research.
ISSN 03600300
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-01-01
Publisher Place New York
e-ISSN 15577341
Journal ACM Computing Surveys (CSUR)
Volume Number 46
Issue Number 3
Page Count 38
Starting Page 1
Ending Page 38

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Source: ACM Digital Library