Please use this identifier to cite or link to this item:
|Title:||Query expansion by spatial co-occurrence for image retrieval|
|Source:||Li, Y.,Geng, B.,Zha, Z.-J.,Li, Y.,Tao, D.,Xu, C. (2011). Query expansion by spatial co-occurrence for image retrieval. MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops : 1177-1180. ScholarBank@NUS Repository. https://doi.org/10.1145/2072298.2071968|
|Abstract:||The well-known bag-of-features (BoF) model is widely utilized for large scale image retrieval. However, BoF model lacks the spatial information of visual words, which is informative for local features to build up meaningful visual patches. To compensate for the spatial information loss, in this paper, we propose a novel query expansion method called Spatial Co-occurrence Query Expansion (SCQE), by utilizing the spatial co-occurrence information of visual words mined from the database images to boost the retrieval performance. In offline phase, for each visual word in the vocabulary, we treat the visual words that are frequently co-occurred with it in the database images as neighbors, base on which a spatial co-occurrence graph is built. In online phase, a query image can be expanded with some spatial co-occurred but unseen visual words according to the spatial co-occurrence graph, and the retrieval performance can be improved by expanding these visual words appropriately. Experimental results demonstrate that, SCQE achieves promising improvements over the typical BoF baseline on two datasets comprising 5K and 505K images respectively. Copyright 2011 ACM.|
|Source Title:||MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 5, 2017
checked on Dec 9, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.