Scene Feature Recognition-Enabled Framework for Mobile Service Information Query System

Zeng, Yi-Chong; Chan, Ya-Hui; Lin, Ting-Yu; Shih, Meng-Jung; Hsieh, Pei-Yu; Chao, Guan-Lin

doi:10.1007/978-3-319-20618-9_7

Cited by 4 publications

(4 citation statements)

References 8 publications

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“…The definition is expanded to a smart city case [59], and applications of smart cities [60]. It is worthwhile to note that the implementation of a recommendation system [61] and an intelligent system including information queries [62,63] is considered a prerequisite system for realizing smart tourism. In addition, essential smart tourism technology was expanded to research on data collection and analysis technology [64][65][66][67], communication technology [68], geomatics and navigation technology [69,70] and app design technology [71].…”

Section: Definition Of Smart Tourismmentioning

confidence: 99%

The Role of Mobile Technology in Tourism: Patents, Articles, News, and Mobile Tour App Reviews

Kim

2017

Sustainability

106

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Abstract:The purpose of this research is to identify the status and role of mobile technology in achieving sustainable and smart tourism, and to suggest future research and strategy directions for academia and managers in practice. This research utilized multiple sources, such as patents, academic articles, and news, and selected methodologies optimized for the purpose of each study. Study 1 used Netminer, a social network analysis program, to analyze the relationships between patent's International Patent Classification (IPC) codes. Study 2 used the T-LAB program for content analysis to analyze the texts of patents, journal articles, and news. Study 3 used the Leximancer program, which utilizes relative frequency to analyze mobile app consumer reviews. In study 1, we identified various forms of data related technologies and mobile technologies for smart city systems and maps. In study 2, we found the environment, sustainability, business, and market themes to be related to mobile technology. In study 3, we explored consumers' attitudes and preferences for mobile travel app using their reviews. Advances in mobile technology are expected to create innovative experiences for consumers, foster a sustainable competitive advantage for tourism destinations and tourism-related suppliers, and create sustainable competencies for smart tourism.

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Section: Definition Of Smart Tourismmentioning

confidence: 99%

The Role of Mobile Technology in Tourism: Patents, Articles, News, and Mobile Tour App Reviews

Kim

2017

Sustainability

106

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“…This approach should provide a transformation method that makes the server unable to judge whether visual features sent from the users are original version or transformed version. The users have to use a relatively simple recognizer that involves no training phase because of their limited computational resources [5] [18]. Where Vi denotes the cluster center, ci denotes the number of pixels in the cluster.…”

Section: E Image Recognizermentioning

confidence: 99%

Enhancing Privacy in Photo Based Location Information Services using Encryption Free Framework

Chandraleka¹

2020

IJRASET

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Mobile devices such as smartphones have been widely used all over the world. In mobile, many applications provide services to the users based on the photos provided by the user. Certain applications, client users take a photo of a certain spot and send it to a server, the server identifies the spot with an image recognizer and returns its related information to the users. It can cause a privacy issue because image recognition results are sometimes privacy sensitive. To overcome the problems of existing approaches, proposed an Encryption-Free framework for Privacy preserving Image Recognition, called Enfpire. Enfpire does not impose any restrictions on the server's recognition algorithm because it does not rely on a cryptographic techniques. In proposed approach user transform the extracted image feature x into y on the user server and sends it to the public server. With the transformation, the effectiveness of the original feature x is degraded so that the public server cannot uniquely recognize the spot-ID of user from y. It only retrives the relevant spot ID's. After that, results are processed by user's server. The unique spot ID will identify and information regarding the spot and relevant images will be given to the user.

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“…virtual 3D model or advertising texts) of the recognized object are overlaid on the camera image for providing information to users. Another example is a tourist assistance system proposed by Zeng et al [12], in which users can get guide information by taking a photo of a landmark, street, building, and so on and sending it to a cloud server that hosts image recognition services.…”

Section: S Ince the Development Of Deep Belief Network Bymentioning

confidence: 99%

“…Client-server-based information services like the one developed in Zeng's work [12] are advantageous in that they can provide the latest information only by updating the server's information database and recognition criteria. However, they can also cause a privacy issue because image recognition results are sometimes privacy-sensitive, whose situation is described in detail in the following subsections.…”

Section: S Ince the Development Of Deep Belief Network Bymentioning

confidence: 99%

Encryption-Free Framework of Privacy-Preserving Image Recognition for Photo-Based Information Services

Nakamura

Nitta

Babaguchi

2019

IEEE Trans.Inform.Forensic Secur.

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Nowadays, mobile devices, such as smartphones, have been widely used all over the world. In addition, the performance of image recognition has drastically increased with deep learning technologies. From these backgrounds, some photobased information services provided in a client-server architecture are getting popular: client users take a photo of a certain spot and send it to a server, while the server identifies the spot with an image recognizer and returns its related information to the users. However, this kind of client-server image recognition can cause a privacy issue because image recognition results are sometimes privacy-sensitive. To tackle the privacy issue, in this paper, we propose a framework of privacy-preserving image recognition called EnfPire, in which the server cannot uniquely determine the recognition result but client users can do so. An overview of EnfPire is as follows. First, client users extract a visual feature from their taken photo and transform it so that the server cannot uniquely determine the recognition result. Then, the users send the transformed feature to the server that returns a set of candidates of the recognition result to the users. Finally, the users compare the candidates to the original visual feature for obtaining the final result. Our experimental results demonstrate that EnfPire successfully degrades the server's spot-recognition accuracy from 99.8% to 41.4% while keeping 86.9% of the spotrecognition accuracy on the user side.

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Scene Feature Recognition-Enabled Framework for Mobile Service Information Query System

Cited by 4 publications

References 8 publications

The Role of Mobile Technology in Tourism: Patents, Articles, News, and Mobile Tour App Reviews

The Role of Mobile Technology in Tourism: Patents, Articles, News, and Mobile Tour App Reviews

Enhancing Privacy in Photo Based Location Information Services using Encryption Free Framework

Encryption-Free Framework of Privacy-Preserving Image Recognition for Photo-Based Information Services

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