MQSearch: Image Search by Multi-Class Query
Refereed conference paper presented and published in conference proceedings


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AbstractImage search is becoming prevalent in web search as the number of digital photos grows exponentially on the internet. For a successful image search system, removing outliers in the top ranked results is a challenging task. Typical content based image search engines take an input image from one class as a query and compute relevance between the query and images in a database. The results often contain a large number of outliers, since these outliers may be similar to the query image in some way. In this paper we present a novel search scheme using query images from multiple classes. Instead of conducting query search for one image class at a time, we conduct multi-class query search jointly. By using several query classes that are similar to each other for multi-class query, we can utilize information across similar classes to fine tune the similarity measure to remove outliers. This strategy can be used for any information search application. In this work, we use content based image search to illustrate the concept.
All Author(s) ListLuo YW, Liu W, Liu JZ, Tang XO
Name of Conference26th Annual CHI Conference on Human Factors in Computing Systems
Start Date of Conference05/04/2008
End Date of Conference10/04/2008
Place of ConferenceFlorence
Country/Region of ConferenceItaly
Year2008
Month1
Day1
PublisherASSOC COMPUTING MACHINERY
Pages49 - 52
ISBN978-1-60558-011-1
LanguagesEnglish-United Kingdom
KeywordsImage Retrieval; Multi-Class; Ranking
Web of Science Subject CategoriesComputer Science; Computer Science, Artificial Intelligence; Computer Science, Software Engineering

Last updated on 2021-14-01 at 23:57