Object Recognition for the Internet of Things

Quack, Till; Bay, Herbert; Gool, Luc Van

doi:10.1007/978-3-540-78731-0_15

Cited by 28 publications

(16 citation statements)

References 17 publications

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“…To avail this functionality many different technologies are used which includes RFID (Radio Frequency Identification), Sensor network technologies, Bluetooth tags, Optical tags and so on. In other words, the development is aimed towards the input devices communicating with other physical objects [4]. Problem of memory and storage can be solved by using various new techniques dedicated to Internet of Things [15].…”

Section: A Internet Of Thingsmentioning

confidence: 99%

Real-Time Object Detection and Recognition Using Internet of Things Paradigm

Jain¹,

Rajankar²

2017

IJIGSP

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Section: A Internet Of Thingsmentioning

confidence: 99%

Real-Time Object Detection and Recognition Using Internet of Things Paradigm

Jain¹,

Rajankar²

2017

IJIGSP

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“…(2) Identifying and sensing technologies in special environment [20]. For example, under deep water, regular electronic tags cannot communicate with readers outside of water, specific tags based on sonar technology should be developed.…”

Section: A Intelligent Identifying and Sensing Technologies In Divermentioning

confidence: 99%

Perspectives on Internet of Things and Its Applications

Xue¹,

Li²,

Liu³

et al. 2012

Proceedings of the 2nd International Conference on Computer Application and System Modeling

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“…It uses the most informative features of each landmark to select the vocabulary and makes it more suitable for large-scale dataset. In [15]- [19], [37], and [38], GPS is first used to tag the large-scale database images for pruning purpose; visual analysis techniques or random sample consensus (RANSAC)-based geometric algorithms are then used to localize the query image. However, the one-to-one matching RANSAC algorithm is computationally intensive.…”

Section: Introductionmentioning

confidence: 99%

“…Even though there are some works [15]- [19] that integrate the context and content analysis for recognition, their integration techniques are still preliminary and the context information used is limited to GPS information only.…”

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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Object Recognition for the Internet of Things

Cited by 28 publications

References 17 publications

Real-Time Object Detection and Recognition Using Internet of Things Paradigm

Real-Time Object Detection and Recognition Using Internet of Things Paradigm

Perspectives on Internet of Things and Its Applications

Integrated Content and Context Analysis for Mobile Landmark Recognition

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