Please use this identifier to cite or link to this item: https://doi.org/10.1145/2393347.2396334
Title: Visual query attributes suggestion
Authors: Bian, J.
Zha, Z.-J. 
Zhang, H.
Tian, Q.
Chua, T.-S. 
Keywords: attribute
image search
query suggestion
Issue Date: 2012
Source: Bian, J.,Zha, Z.-J.,Zhang, H.,Tian, Q.,Chua, T.-S. (2012). Visual query attributes suggestion. MM 2012 - Proceedings of the 20th ACM International Conference on Multimedia : 869-872. ScholarBank@NUS Repository. https://doi.org/10.1145/2393347.2396334
Abstract: Query suggestion is an effective solution to help users deliver their search intent. While many query suggestion approaches have been proposed for test-based image retrieval with query-by-keywords, query suggestion for content-based image retrieval (CBIR) with query-by-example (QBE) has been seldom studied. QBE usually suffers from the "intention gap" problem, especially when the user fails to get an appropriate query image to express his search intention precisely. In this paper, we propose a novel query suggestion scheme named Visual Query Attributes Suggestion (VQAS) for image search with QBE. Given a query image, informative attributes are suggested to the user as complements to the query. These attributes reflect the visual properties and key components of the query. By selecting some suggested attributes, the user can provide more precise search intent which is not captured by the query image. The evaluation results on two real-world image datasets show the effectiveness of VQAS in terms of retrieval performance and the quality of query suggestions. © 2012 ACM.
Source Title: MM 2012 - Proceedings of the 20th ACM International Conference on Multimedia
URI: http://scholarbank.nus.edu.sg/handle/10635/42194
ISBN: 9781450310895
DOI: 10.1145/2393347.2396334
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