Location discriminative vocabulary coding for mobile landmark search
With the popularization of mobile devices, recent years have witnessed an emerging potential for mobile landmark search. In this scenario, the user experience heavily depends on the efficiency of query transmission over a wireless link. As sending a query photo is time consuming, recent works have p...
| Main Authors: | , , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
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2013
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| Online Access: | https://hdl.handle.net/10356/104157 http://hdl.handle.net/10220/16979 |
| _version_ | 1811683351870832640 |
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| author | Yao, Hongxun Yuan, Junsong Rui, Yong Gao, Wen Ji, Rongrong Duan, Ling-Yu Chen, Jie |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Yao, Hongxun Yuan, Junsong Rui, Yong Gao, Wen Ji, Rongrong Duan, Ling-Yu Chen, Jie |
| author_sort | Yao, Hongxun |
| collection | NTU |
| description | With the popularization of mobile devices, recent years have witnessed an emerging potential for mobile landmark search. In this scenario, the user experience heavily depends on the efficiency of query transmission over a wireless link. As sending a query photo is time consuming, recent works have proposed to extract compact visual descriptors directly on the mobile end towards low bit rate transmission. Typically, these descriptors are extracted based solely on the visual content of a query, and the location cues from the mobile end are rarely exploited. In this paper, we present a Location Discriminative Vocabulary Coding (LDVC) scheme, which achieves extremely low bit rate query transmission, discriminative landmark description, as well as scalable descriptor delivery in a unified framework. Our first contribution is a compact and location discriminative visual landmark descriptor, which is offline learnt in two-step: First, we adopt spectral clustering to segment a city map into distinct geographical regions, where both visual and geographical similarities are fused to optimize the partition of city-scale geo-tagged photos. Second, we propose to learn LDVC in each region with two schemes: (1) a Ranking Sensitive PCA and (2) a Ranking Sensitive Vocabulary Boosting. Both schemes embed location cues to learn a compact descriptor, which minimizes the retrieval ranking loss by replacing the original high-dimensional signatures. Our second contribution is a location aware online vocabulary adaption: We store a single vocabulary in the mobile end, which is efficiently adapted for a region specific LDVC coding once a mobile device enters a given region. The learnt LDVC landmark descriptor is extremely compact (typically 10–50 bits with arithmetical coding) and performs superior over state-of-the-art descriptors. We implemented the framework in a real-world mobile landmark search prototype, which is validated in a million-scale landmark database covering typical areas e.g. Beijing, New York City, Lhasa, Singapore, and Florence. |
| first_indexed | 2024-10-01T04:11:22Z |
| format | Journal Article |
| id | ntu-10356/104157 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:11:22Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/1041572020-03-07T14:00:37Z Location discriminative vocabulary coding for mobile landmark search Yao, Hongxun Yuan, Junsong Rui, Yong Gao, Wen Ji, Rongrong Duan, Ling-Yu Chen, Jie School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing With the popularization of mobile devices, recent years have witnessed an emerging potential for mobile landmark search. In this scenario, the user experience heavily depends on the efficiency of query transmission over a wireless link. As sending a query photo is time consuming, recent works have proposed to extract compact visual descriptors directly on the mobile end towards low bit rate transmission. Typically, these descriptors are extracted based solely on the visual content of a query, and the location cues from the mobile end are rarely exploited. In this paper, we present a Location Discriminative Vocabulary Coding (LDVC) scheme, which achieves extremely low bit rate query transmission, discriminative landmark description, as well as scalable descriptor delivery in a unified framework. Our first contribution is a compact and location discriminative visual landmark descriptor, which is offline learnt in two-step: First, we adopt spectral clustering to segment a city map into distinct geographical regions, where both visual and geographical similarities are fused to optimize the partition of city-scale geo-tagged photos. Second, we propose to learn LDVC in each region with two schemes: (1) a Ranking Sensitive PCA and (2) a Ranking Sensitive Vocabulary Boosting. Both schemes embed location cues to learn a compact descriptor, which minimizes the retrieval ranking loss by replacing the original high-dimensional signatures. Our second contribution is a location aware online vocabulary adaption: We store a single vocabulary in the mobile end, which is efficiently adapted for a region specific LDVC coding once a mobile device enters a given region. The learnt LDVC landmark descriptor is extremely compact (typically 10–50 bits with arithmetical coding) and performs superior over state-of-the-art descriptors. We implemented the framework in a real-world mobile landmark search prototype, which is validated in a million-scale landmark database covering typical areas e.g. Beijing, New York City, Lhasa, Singapore, and Florence. 2013-10-28T07:21:15Z 2019-12-06T21:27:35Z 2013-10-28T07:21:15Z 2019-12-06T21:27:35Z 2012 2012 Journal Article Ji, R., Duan, L. Y., Chen, J., Yao, H., Yuan, J., Rui, Y., et al. (2012). Location discriminative vocabulary coding for mobile landmark search. International journal of computer vision, 96(3), 290-314. 0920-5691 https://hdl.handle.net/10356/104157 http://hdl.handle.net/10220/16979 10.1007/s11263-011-0472-9 en International journal of computer vision |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Yao, Hongxun Yuan, Junsong Rui, Yong Gao, Wen Ji, Rongrong Duan, Ling-Yu Chen, Jie Location discriminative vocabulary coding for mobile landmark search |
| title | Location discriminative vocabulary coding for mobile landmark search |
| title_full | Location discriminative vocabulary coding for mobile landmark search |
| title_fullStr | Location discriminative vocabulary coding for mobile landmark search |
| title_full_unstemmed | Location discriminative vocabulary coding for mobile landmark search |
| title_short | Location discriminative vocabulary coding for mobile landmark search |
| title_sort | location discriminative vocabulary coding for mobile landmark search |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing |
| url | https://hdl.handle.net/10356/104157 http://hdl.handle.net/10220/16979 |
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