title: Image Location Estimation by Salient Region Matching.
abstract: Nowadays, locations of images have been widely used in many application scenarios for large geo-tagged image corpora. As to images which are not geographically tagged, we estimate their locations with the help of the large geo-tagged image set by content-based image retrieval. In this paper, we exploit spatial information of useful visual words to improve image location estimation (or content-based image retrieval performances). We proposed to generate visual word groups by mean-shift clustering. To improve the retrieval performance, spatial constraint is utilized to code the relative position of visual words. We proposed to generate a position descriptor for each visual word and build fast indexing structure for visual word groups. Experiments show the effectiveness of our proposed approach.
authors.forename: Xueming
authors.initials: X
authors.lastname: Qian
authors.forename: Yisi
authors.initials: Y
authors.lastname: Zhao
authors.forename: Junwei
authors.initials: J
authors.lastname: Han