research-article

Evaluating Pre-Processing Pipelines for Thermal-Visual Smart Camera

Authors:

Irida Shallari,

Muhammad Imran,

Mattias O'NilsAuthors Info & Claims

ICDSC 2017: Proceedings of the 11th International Conference on Distributed Smart Cameras

Pages 95 - 100

https://doi.org/10.1145/3131885.3131908

Published: 05 September 2017 Publication History

Abstract

Smart camera systems integrating multi-model image sensors provide better spectral sensitivity and hence better pass-fail decisions. In a given vision system, pre-processing tasks have a ripple effect on output data and pass-fail decision of high level tasks such as feature extraction, classification and recognition. In this work, we investigated four pre-processing pipelines and evaluated the effect on classification accuracy and output transmission data. The pre-processing pipelines processed four types of images, thermal grayscale, thermal binary, visual and visual binary. The results show that the pre-processing pipeline, which transmits visual compressed Region of Interest (ROI) images, offers 13 to 64 percent better classification accuracy as compared to thermal grayscale, thermal binary and visual binary. The results show that visual raw and visual compressed ROI with suitable quantization matrix offers similar classification accuracy but visual compressed ROI offers up to 99 percent reduced communication data as compared to visual ROI.

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Cited By

Can OKantarci SUnal G(2021)A New Approach to Use Modern Object Detection Methods More Efficiently on CCTV Systems2021 6th International Conference on Computer Science and Engineering (UBMK)10.1109/UBMK52708.2021.9558899(623-628)Online publication date: 15-Sep-2021
https://doi.org/10.1109/UBMK52708.2021.9558899
Shallari IKrug SO'Nils MEsterle LPrati AVelipasalar SBrea VShan C(2018)Architectural evaluation of nodeProceedings of the 12th International Conference on Distributed Smart Cameras10.1145/3243394.3243688(1-6)Online publication date: 3-Sep-2018
https://dl.acm.org/doi/10.1145/3243394.3243688

Index Terms

Evaluating Pre-Processing Pipelines for Thermal-Visual Smart Camera
1. Computer systems organization
  1. Real-time systems
    1. Real-time system architecture
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object detection

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cover image ACM Other conferences

ICDSC 2017: Proceedings of the 11th International Conference on Distributed Smart Cameras

September 2017

221 pages

ISBN:9781450354875

DOI:10.1145/3131885

Copyright © 2017 ACM.

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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Stanford University: Stanford University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 September 2017

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ICDSC 2017

ICDSC 2017: International Conference on Distributed Smart Cameras

September 5 - 7, 2017

CA, Stanford, USA

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Overall Acceptance Rate 92 of 117 submissions, 79%

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Cited By

Can OKantarci SUnal G(2021)A New Approach to Use Modern Object Detection Methods More Efficiently on CCTV Systems2021 6th International Conference on Computer Science and Engineering (UBMK)10.1109/UBMK52708.2021.9558899(623-628)Online publication date: 15-Sep-2021
https://doi.org/10.1109/UBMK52708.2021.9558899
Shallari IKrug SO'Nils MEsterle LPrati AVelipasalar SBrea VShan C(2018)Architectural evaluation of nodeProceedings of the 12th International Conference on Distributed Smart Cameras10.1145/3243394.3243688(1-6)Online publication date: 3-Sep-2018
https://dl.acm.org/doi/10.1145/3243394.3243688

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