A PDA-Based System for Recognizing Buildings from User-Supplied Images

Mai, Wanji; Dodds, G.; Tweed, Christopher

doi:10.1007/978-3-540-24641-1_11

Cited by 7 publications

(7 citation statements)

References 8 publications

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“…This is identical in concept to cell-ID, in that a mobile phone's location is determined to be that of the centre of the 'cell' (the mobile tower). Research is also being undertaken into the automated recognition scenes from image databases (Xu et al 2003, Mai et al 2004. Another method is 'map matching' where Journal of Location Based Services 11 positioning information derived from a navigation sensor is then augmented by map data that constrains a vehicle's position to the road network as defined by road centreline data contained within a GIS.…”

Section: Science and Technologies Of Importance To Lbsmentioning

confidence: 99%

A critical evaluation of location based services and their potential

Raper

Gärtner

Karimi

et al. 2007

Journal of Location Based Services

132

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This Editorial lead article for the Journal of Location Based Services surveys this complex and multi-disciplinary field and identifies the key research issues. Although this field has produced early commercial disappointments, the inevitability that pervasive location-aware services on mobile devices will emerge means that much research is needed to inform these developments. The article reviews firstly: the science and technology of positioning, geographic information science, mobile cartography, spatial cognition and interfaces, information science, ubiquitous computing; and secondly the business, content and legal, social and ethics aspects, before synthesising the key issues for this new field.

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Section: Science and Technologies Of Importance To Lbsmentioning

confidence: 99%

A critical evaluation of location based services and their potential

Raper

Gärtner

Karimi

et al. 2007

Journal of Location Based Services

132

View full text Add to dashboard Cite

show abstract

“…An information augmentation system (infoScope) [35] has been developed which uses a GPS sensor to obtain locations, performs image matching, and superimposes the information associated with buildings or places into the real scene image. A mobile tourist information prototype has been developed in [36]. It uses the contextual information of GPS and orientation data and matches the query image with various orientations using a 3D model.…”

Section: IImentioning

confidence: 99%

A Survey on Mobile Landmark Recognition for Information Retrieval

Chen

Yap

et al. 2009

2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware

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The growing usage of mobile devices has led to proliferation of many mobile applications. A growing trend in mobile applications is centered on mobile landmark recognition. It is a new mobile application that recognizes a captured landmark using the mobile device and retrieves related information. This paper will present a survey on mobile landmark recognition for information retrieval. A general overview of existing mobile landmark recognition systems will be summarized. The techniques and algorithms used in the literatures, including content analysis of landmarks and classification methods for recognition, will be described.

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“…As mobile phones with imaging capability are becoming more prevalent, a few works that focus on mobile scene/landmark recognition [9]- [12] have been developed recently. A content-based image recognition approach using mobile devices has been developed in [9].…”

Section: Introductionmentioning

confidence: 99%

“…Informative SIFT [10] and discriminative patch-based [11] content analysis are adopted for similarity matching. A mobile tourist information prototype has been developed in [12]. It uses the global positioning system (GPS) information and 3-D model to match the query image.…”

Section: Introductionmentioning

confidence: 99%

Integrated Content and Context Analysis for Mobile Landmark Recognition

Chen

Yap

Chau

2011

IEEE Trans. Circuits Syst. Video Technol.

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This paper proposes a new approach for mobile landmark recognition based on integrated content and context analysis. Conventional scene/landmark recognition methods focus mainly on nonmobile desktop/PC platform, where content analysis alone is used to perform landmark recognition. These nonmobile systems, however, do not take unique features of mobile devices into consideration, e.g., limited computational power and fast response time requirement of mobile users. On the contrary, most existing context-aware content mobile landmark recognition methods mainly rely on global positioning system location information for context analysis. In view of this, this paper proposes an effective method that employs an integration of content and context analysis to perform landmark recognition using mobile devices. A new bags-of-words (BoW) framework is developed to perform content analysis. It is then integrated with context analysis involving fusion of location and direction information to perform mobile landmark recognition.Experimental results based on the NTU50Landmark database show that the proposed method can achieve good recognition performance in mobile landmark recognition.

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A PDA-Based System for Recognizing Buildings from User-Supplied Images

Cited by 7 publications

References 8 publications

A critical evaluation of location based services and their potential

A critical evaluation of location based services and their potential

A Survey on Mobile Landmark Recognition for Information Retrieval

Integrated Content and Context Analysis for Mobile Landmark Recognition

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