%0 Conference Proceedings
%T A Novel Model for Semantic Learning and Retrieval of Images
%+ College of Computer Science and Information Technology
%+ Collège of information Engineering (CIE)
%+ College of Information Engineering [Xiangtan University]
%A Li, Zhixin
%A Shi, Zhiping
%A Tang, Zhengjun
%A Zhao, Weizhong
%Z Part 11: Image Processing
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 7th International Conference on Intelligent Information Processing (IIP)
%C Guilin, China
%Y Zhongzhi Shi
%Y David Leake
%Y Sunil Vadera
%I Springer
%3 Intelligent Information Processing VI
%V AICT-385
%P 337-346
%8 2012-10-12
%D 2012
%R 10.1007/978-3-642-32891-6_42
%K semantic learning
%K automatic image annotation
%K continuous PLSA
%K aspect model
%K image retrieval
%Z Computer Science [cs]Conference papers
%X In this paper, we firstly propose an extended probabilistic latent semantic analysis (PLSA) to model continuous quantity. In addition, corresponding EM algorithm is derived to determine the parameters. Then, we apply this model in automatic image annotation. In order to deal with the data of different modalities according to their characteristics, we present a semantic annotation model which employs continuous PLSA and traditional PLSA to model visual features and textual words respectively. These two models are linked with the same distribution over all aspects. Furthermore, an asymmetric learning approach is adopted to estimate the model parameters. This model can predict semantic annotation well for an unseen image because it associates visual and textual modalities more precisely and effectively. We evaluate our approach on the Corel5k and Corel30k dataset. The experiment results show that our approach outperforms several state-of-the-art approaches.
%G English
%Z TC 12
%2 https://inria.hal.science/hal-01524960/document
%2 https://inria.hal.science/hal-01524960/file/978-3-642-32891-6_42_Chapter.pdf
%L hal-01524960
%U https://inria.hal.science/hal-01524960
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC12
%~ IFIP-IIP
%~ IFIP-AICT-385