Please use this identifier to cite or link to this item:
https://doi.org/10.1145/2502081.2502093
DC Field | Value | |
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dc.title | Attribute-augmented semantic hierarchy: Towards bridging semantic gap and intention gap in image retrieval | |
dc.contributor.author | Zhang, H. | |
dc.contributor.author | Zha, Z.-J. | |
dc.contributor.author | Yang, Y. | |
dc.contributor.author | Yan, S. | |
dc.contributor.author | Gao, Y. | |
dc.contributor.author | Chua, T.-S. | |
dc.date.accessioned | 2014-10-07T04:41:57Z | |
dc.date.available | 2014-10-07T04:41:57Z | |
dc.date.issued | 2013 | |
dc.identifier.citation | Zhang, H.,Zha, Z.-J.,Yang, Y.,Yan, S.,Gao, Y.,Chua, T.-S. (2013). Attribute-augmented semantic hierarchy: Towards bridging semantic gap and intention gap in image retrieval. MM 2013 - Proceedings of the 2013 ACM Multimedia Conference : 33-42. ScholarBank@NUS Repository. <a href="https://doi.org/10.1145/2502081.2502093" target="_blank">https://doi.org/10.1145/2502081.2502093</a> | |
dc.identifier.isbn | 9781450324045 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/83502 | |
dc.description.abstract | This paper presents a novel Attribute-augmented Seman- Tic Hierarchy (A2SH) and demonstrates its effectiveness in bridging both the semantic and intention gaps in Content- based Image Retrieval (CBIR). A 2SH organizes the seman- Tic concepts into multiple semantic levels and augments each concept with a set of related attributes, which describe the multiple facets of the concept and act as the intermedi- Ate bridge connecting the concept and low-level visual con- Tent. A hierarchical semantic similarity function is learnt to characterize the semantic similarities among images for re- Trieval. To better capture user search intent, a hybrid feed- back mechanism is developed, which collects hybrid feed- backs on attributes and images. These feedbacks are then used to refine the search results based on A2SH. We de- velop a content-based image retrieval system based on the proposed A 2SH. We conduct extensive experiments on a large-scale data set of over one million Web images. Exper- imental results show that the proposed A2SH can charac- Terize the semantic affinities among images accurately and can shape user search intent precisely and quickly, leading to more accurate search results as compared to state-of-the-art CBIR solutions. Copyright © 2013 ACM. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1145/2502081.2502093 | |
dc.source | Scopus | |
dc.subject | Attribute | |
dc.subject | Image retrieval | |
dc.subject | Semantic hierarchy | |
dc.type | Conference Paper | |
dc.contributor.department | COMPUTER SCIENCE | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.description.doi | 10.1145/2502081.2502093 | |
dc.description.sourcetitle | MM 2013 - Proceedings of the 2013 ACM Multimedia Conference | |
dc.description.page | 33-42 | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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