A lexica family with small semantic GAP

Authors:
Jiemin Liu;Qi Tian;Yijuan Lu;Changhu Wang;Lei Zhang;Xiaokang Yang;Shipeng Li
Affiliations:
Microsoft Research Asia, Beijing, China and Department of Electronic Engineering, Shanghai Jiao Tong University;Microsoft Research Asia, Beijing, China;Department of Computer Science, Texas State University;Microsoft Research Asia, Beijing, China;Microsoft Research Asia, Beijing, China;Department of Electronic Engineering, Shanghai Jiao Tong University;Microsoft Research Asia, Beijing, China
Venue:
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Year:
2009

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Abstract

Defining a lexicon of high-level concepts is the first step for data collection and model construction in concept-based image retrieval. Differences of semantic gaps among concepts are well worth considering. By measuring consistency in visual space and textual space, concepts with small semantic gap can be obtained. Considering so many diverse concepts in large-scale image dataset, we construct a lexica family of high-level concepts with small semantic gap based on different low-level features and different consistency measurements. In this lexica family, the lexica are independent to each other and mutually complementary. It provides helpful suggestions about data collection, feature selection and search model construction for large-scale image retrieval.