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Tag-based image retrieval improved by augmented features and group-based refinement

หน่วยงาน Nanyang Technological University, Singapore

รายละเอียด

ชื่อเรื่อง : Tag-based image retrieval improved by augmented features and group-based refinement
นักวิจัย : Chen, Lin , Xu, Dong , Tsang, Ivor Wai-Hung , Luo, Jiebo
คำค้น : DRNTU::Engineering::Computer science and engineering
หน่วยงาน : Nanyang Technological University, Singapore
ผู้ร่วมงาน : -
ปีพิมพ์ : 2555
อ้างอิง : Chen, L., Xu, D., Tsang, I. W., & Luo, J. (2012). Tag-Based Image Retrieval Improved by Augmented Features and Group-Based Refinement. IEEE Transactions on Multimedia, 14(4), 1057-1067. , 1520-9210 , http://hdl.handle.net/10220/11473 , http://dx.doi.org/10.1109/TMM.2012.2187435
ที่มา : -
ความเชี่ยวชาญ : -
ความสัมพันธ์ : IEEE transactions on multimedia
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

In this paper, we propose a new tag-based image retrieval framework to improve the retrieval performance of a group of related personal images captured by the same user within a short period of an event by leveraging millions of training web images and their associated rich textual descriptions. For any given query tag (e.g., “car”), the inverted file method is employed to automatically determine the relevant training web images that are associated with the query tag and the irrelevant training web images that are not associated with the query tag. Using these relevant and irrelevant web images as positive and negative training data respectively, we propose a new classification method called support vector machine (SVM) with augmented features (AFSVM) to learn an adapted classifier by leveraging the prelearned SVM classifiers of popular tags that are associated with a large number of relevant training web images. Treating the decision values of one group of test photos from AFSVM classifiers as the initial relevance scores, in the subsequent group-based refinement process, we propose to use the Laplacian regularized least squares method to further refine the relevance scores of test photos by utilizing the visual similarity of the images within the group. Based on the refined relevance scores, our proposed framework can be readily applied to tag-based image retrieval for a group of raw consumer photos without any textual descriptions or a group of Flickr photos with noisy tags. Moreover, we propose a new method to better calculate the relevance scores for Flickr photos. Extensive experiments on two datasets demonstrate the effectiveness of our framework.

บรรณานุกรม :
Chen, Lin , Xu, Dong , Tsang, Ivor Wai-Hung , Luo, Jiebo . (2555). Tag-based image retrieval improved by augmented features and group-based refinement.
    กรุงเทพมหานคร : Nanyang Technological University, Singapore.
Chen, Lin , Xu, Dong , Tsang, Ivor Wai-Hung , Luo, Jiebo . 2555. "Tag-based image retrieval improved by augmented features and group-based refinement".
    กรุงเทพมหานคร : Nanyang Technological University, Singapore.
Chen, Lin , Xu, Dong , Tsang, Ivor Wai-Hung , Luo, Jiebo . "Tag-based image retrieval improved by augmented features and group-based refinement."
    กรุงเทพมหานคร : Nanyang Technological University, Singapore, 2555. Print.
Chen, Lin , Xu, Dong , Tsang, Ivor Wai-Hung , Luo, Jiebo . Tag-based image retrieval improved by augmented features and group-based refinement. กรุงเทพมหานคร : Nanyang Technological University, Singapore; 2555.