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HyperCam: hyperspectral imaging for ubiquitous computing applications

Published: 07 September 2015 Publication History

Abstract

Emerging uses of imaging technology for consumers cover a wide range of application areas from health to interaction techniques; however, typical cameras primarily transduce light from the visible spectrum into only three overlapping components of the spectrum: red, blue, and green. In contrast, hyperspectral imaging breaks down the electromagnetic spectrum into more narrow components and expands coverage beyond the visible spectrum. While hyperspectral imaging has proven useful as an industrial technology, its use as a sensing approach has been fragmented and largely neglected by the UbiComp community. We explore an approach to make hyperspectral imaging easier and bring it closer to the end-users. HyperCam provides a low-cost implementation of a multispectral camera and a software approach that automatically analyzes the scene and provides a user with an optimal set of images that try to capture the salient information of the scene. We present a number of use-cases that demonstrate HyperCam's usefulness and effectiveness.

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    cover image ACM Conferences
    UbiComp '15: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing
    September 2015
    1302 pages
    ISBN:9781450335744
    DOI:10.1145/2750858
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 07 September 2015

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    Author Tags

    1. computer vision
    2. multispectral imaging
    3. sensing

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    • Research-article

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    UbiComp '15
    Sponsor:
    • Yahoo! Japan
    • SIGMOBILE
    • FX Palo Alto Laboratory, Inc.
    • ACM
    • Rakuten Institute of Technology
    • Microsoft
    • Bell Labs
    • SIGCHI
    • Panasonic
    • Telefónica
    • ISTC-PC

    Acceptance Rates

    UbiComp '15 Paper Acceptance Rate 101 of 394 submissions, 26%;
    Overall Acceptance Rate 764 of 2,912 submissions, 26%

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    • (2024)MeatSpec: Enabling Ubiquitous Meat Fraud Inspection through Consumer-Level Spectral ImagingProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3690666(861-874)Online publication date: 4-Dec-2024
    • (2024)HPRN: Holistic Prior-Embedded Relation Network for Spectral Super-ResolutionIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2023.326082835:8(11409-11423)Online publication date: Aug-2024
    • (2024)Learning to Recover Spectral Reflectance From RGB ImagesIEEE Transactions on Image Processing10.1109/TIP.2024.339339033(3174-3186)Online publication date: 2024
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    • (2024)Auto-Encoder Guided Attention Based Network for Hyperspectral Recovery from Real RGB ImagesPattern Recognition and Machine Intelligence10.1007/978-3-031-12700-7_5(42-52)Online publication date: 24-Jul-2024
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    • (2023)Multispectral Image Processing System for Precision Detection of Reheated Coconut OilWSEAS TRANSACTIONS ON SIGNAL PROCESSING10.37394/232014.2023.19.2119(200-204)Online publication date: 31-Dec-2023
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