Automatic Image Annotation and Retrieval Using Hybrid Approach

摘要：

　　We firstly propose continuous probabilistic latent semantic analysis (PLSA) to model continuous quantity.In addition,corresponding Expectation-Maximization (EM) algorithm is derived to determine the model parameters.Furthermore,we present a hybrid framework which employs continuous PLSA to model visual features of images in generative learning stage and uses ensembles of classifier chains to classify the multi-label data in discriminative learning stage.Since the framework combines the advantages of generative and discriminative learning,it can predict semantic annotation precisely for unseen images.Finally,we conduct a series of experiments on a standard Corel dataset.The experiment results show that our approach outperforms many state-of-the-art approaches.

关键词： automatic image annotation continuous PLSA semantic learning hybrid approach image retrieval

作者: Zhixin Li Weizhong Zhao Zhiqing Li Zhiping Shi

作者单位: College of Computer Science and Information Technology,Guangxi Normal University,Guilin 541004,China College of Information Engineering,Xiangtan University,Xiangtan 411105,China College of Information Engineering,Capital Normal University,Beijing 100048,China

会议类型: 国际会议

会议名称: 7th IFIP TC 12 International Conference (第七届智能信息处理国际会议 (IIP 2012))

会议地点: 桂林

会议语种:英文

页码: 347-356

在线出版日期: 2012-10-12（万方平台首次上网日期，不代表论文的发表时间）