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...

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Main Authors: Yao, Hongxun, Yuan, Junsong, Rui, Yong, Gao, Wen, Ji, Rongrong, Duan, Ling-Yu, Chen, Jie
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2013
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Online Access:https://hdl.handle.net/10356/104157
http://hdl.handle.net/10220/16979
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.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
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
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
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.
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
format Article
author Yao, Hongxun
Yuan, Junsong
Rui, Yong
Gao, Wen
Ji, Rongrong
Duan, Ling-Yu
Chen, Jie
author_sort Yao, Hongxun
title Location discriminative vocabulary coding for mobile landmark search
title_short 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_sort location discriminative vocabulary coding for mobile landmark search
publishDate 2013
url https://hdl.handle.net/10356/104157
http://hdl.handle.net/10220/16979
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