Spectral-360: A Physics-Based Technique for Change Detection

Conference paper


Sedky, Mohamed, Moniri, M. and Chibelushi, Claude C. 2014. Spectral-360: A Physics-Based Technique for Change Detection. 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2014). Columbus, OH, USA 23 - 28 Jun 2014 IEEE. pp. 405-408 https://doi.org/10.1109/CVPRW.2014.65
AuthorsSedky, Mohamed, Moniri, M. and Chibelushi, Claude C.
TypeConference paper
Abstract

This paper presents and assesses a novel physics-based change detection technique, Spectral-360, which is based on the dichromatic color reflectance model. This approach, uses image formation models to computationally estimate, from the camera output, a consistent physics-based color descriptor of the spectral reflectance of surfaces visible in the image, and then to measure the similarity between the full-spectrum reflectance of the background and foreground pixels to segment the foreground from a static background. This method represents a new approach to change detection, using explicit hypotheses about the physics that create images. The assumptions which have been made are that diffuse-only-reflection is applicable, and the existence of a dominant illuminant. The objective evaluation performed using the 'changedetection.net 2014' dataset shows that our Spectral-360 method outperforms most state-of-the-art methods.

Year2014
Conference2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2014)
PublisherIEEE
Publication dates
Print25 Sep 2014
Publication process dates
Deposited22 Aug 2017
ISSN2160-7516
Book title2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops
ISBN978-1-4799-4308-1
Digital Object Identifier (DOI)https://doi.org/10.1109/CVPRW.2014.65
Web address (URL)https://doi.org/10.1109/CVPRW.2014.65
Page range405-408
Permalink -

https://repository.uel.ac.uk/item/858x9

  • 171
    total views
  • 0
    total downloads
  • 1
    views this month
  • 0
    downloads this month

Export as

Related outputs

A Frequency Bin Analysis of Distinctive Ranges Between Human and Deepfake Generated Voices
Maltby, H., Wall, J., Glackin, C., Moniri, M., Cannings, N. and Salami, I. 2024. A Frequency Bin Analysis of Distinctive Ranges Between Human and Deepfake Generated Voices. 2024 International Joint Conference on Neural Networks (IJCNN) - Neural Networks Models. Yokohama, Japan 30 Jun - 05 Jul 2024 IEEE.
Enhancing Automatic Speech Recognition Quality with a Second-Stage Speech Enhancement Generative Adversarial Network
Nossier, S. A., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2023. Enhancing Automatic Speech Recognition Quality with a Second-Stage Speech Enhancement Generative Adversarial Network. The 35th IEEE International Conference on Tools with Artificial Intelligence (ICTAI). Atlanta, Georgia (USA) 06 - 08 Nov 2023 IEEE Computer Society. https://doi.org/10.1109/ICTAI59109.2023.00087
A Deep Learning Speech Enhancement Architecture Optimised for Speech Recognition and Hearing Aids
Nossier, S. A., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2023. A Deep Learning Speech Enhancement Architecture Optimised for Speech Recognition and Hearing Aids. The 35th IEEE International Conference on Tools with Artificial Intelligence (ICTAI). Atlanta, Georgia (USA) 06 - 08 Nov 2023 IEEE Computer Society. https://doi.org/10.1109/ICTAI59109.2023.00088
An Extended Reality Solution for Mitigating the Video Fatigue of Online Meetings
Glackin, C., Cannings, N., Poobalasingam, V., Wall, J., Sharif, S. and Moniri, M. 2023. An Extended Reality Solution for Mitigating the Video Fatigue of Online Meetings. in: Jung, T. and tom Dieck, M. C. (ed.) XR-Metaverse Cases: Business Application of AR, VR, XR and Metaverse Springer. pp. 45-54
Short Utterance Dialogue Act Classification Using a Transformer Ensemble
Maltby, H., Wall, J., Goodluck Constance, T., Moniri, M., Glackin, C., Rajwadi, M. and Cannings, N. 2023. Short Utterance Dialogue Act Classification Using a Transformer Ensemble. UA-DIGITAL 2023: UA Digital Theme Research Twinning. Online virtual conference 27 - 31 Mar 2023
Deception Detection in Conversations using the Proximity of Linguistic Markers
Bajaj, N., Rajwadi, M., Goodluck Constance, T., Wall, J., Moniri, M., Laird, T., Woodruff, C., Laird, J., Glackin, C. and Cannings, N. 2023. Deception Detection in Conversations using the Proximity of Linguistic Markers. Knowledge-Based Systems. 23 (Art. 110422). https://doi.org/10.1016/j.knosys.2023.110422
Convolutional Recurrent Smart Speech Enhancement Architecture for Hearing Aids
Abdallah Abdelhafiz Nossier, S., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2022. Convolutional Recurrent Smart Speech Enhancement Architecture for Hearing Aids. INTERSPEECH 2022. Incheon, Korea 18 - 22 Sep 2022
Two-Stage Deep Learning Approach for Speech Enhancement and Reconstruction in The Frequency and Time Domains
Nossier, S. A., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2022. Two-Stage Deep Learning Approach for Speech Enhancement and Reconstruction in The Frequency and Time Domains. WCCI 2022: IEEE World Congress on Computational Intelligence. Padua, Italy 23 May - 18 Jul 2022 IEEE. https://doi.org/10.1109/IJCNN55064.2022.9892355
A Mixed Reality Approach for dealing with the Video Fatigue of Online Meetings
Wall, J., Poobalasingam, V., Sharif, S., Moniri, M., Glackin, C. and Cannings, N. 2022. A Mixed Reality Approach for dealing with the Video Fatigue of Online Meetings. 7th International XR Conference. Lisbon, Portugal 27 - 29 Apr 2022
Resolving Ambiguity in Hedge Detection by Automatic Generation of Linguistic Rules
Goodluck Constance, T., Bajaj, N., Rajwadi, M., Maltby, H., Wall, J., Moniri, M., Woodruff, C., Laird, T., Laird, J., Glackin, C. and Cannings, N. 2021. Resolving Ambiguity in Hedge Detection by Automatic Generation of Linguistic Rules. 30th International Conference on Artificial Neural Networks (ICANN). Online 14 - 17 Sep 2021 Springer. https://doi.org/10.1007/978-3-030-86383-8_30
An Experimental Analysis of Deep Learning Architectures for Supervised Speech Enhancement
Nossier, S. A., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2020. An Experimental Analysis of Deep Learning Architectures for Supervised Speech Enhancement. Electronics. 10 (Art. 17). https://doi.org/10.3390/electronics10010017
Mapping and Masking Targets Comparison using Different Deep Learning based Speech Enhancement Architectures
Abdallah Abdelhafiz Nossier, S., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2020. Mapping and Masking Targets Comparison using Different Deep Learning based Speech Enhancement Architectures. 2020 International Joint Conference on Neural Networks (IJCNN). Glasgow, UK 19 - 24 Jul 2020 IEEE. https://doi.org/10.1109/IJCNN48605.2020.9206623
A Comparative Study of Time and Frequency Domain Approaches to Deep Learning based Speech Enhancement
Abdallah Abdelhafiz Nossier, S., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2020. A Comparative Study of Time and Frequency Domain Approaches to Deep Learning based Speech Enhancement. 2020 International Joint Conference on Neural Networks (IJCNN). Glasgow, UK 19 - 24 Jul 2020 IEEE. https://doi.org/10.1109/IJCNN48605.2020.9206928
Fraud detection in telephone conversations for financial services using linguistic features
Bajaj, N., Goodluck Constance, T., Rajwadi, M., Wall, J., Moniri, M., Glackin, C., Cannings, N., Woodruff, C. and Laird, J. 2019. Fraud detection in telephone conversations for financial services using linguistic features. Neural Information Processing Systems - NeurIPS 2019. Vancouver, Canada 08 - 14 Dec 2019 NeurIPS.
A Framework for Augmented Reality Based Shared Experiences
Ali, A., Glackin, C., Cannings, N., Wall, J., Sharif, S. and Moniri, M. 2019. A Framework for Augmented Reality Based Shared Experiences. Immersive Learning Research Network - iLRN. London, UK 23 - 27 Jun 2019 Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-657-4-24
Comparative Analysis on the Competitiveness of Conventional and Compressive Sensing-based Query Processing
Fayed, Salema, Youssef, Sherin, El-Helw, Amr, Akbari, Akbar Sheikh, Patwary, Mohammad and Moniri, M. 2014. Comparative Analysis on the Competitiveness of Conventional and Compressive Sensing-based Query Processing. in: Advances in Information Science and Applications, Volume 1: Proceedings of the 18th International Conference on Computers (part of CSCC '14) Institute for Natural Sciences and Engineering (INASE).
Evaluation of Performance Enhancement for Crash Constellation Prediction via Car-to-Car Communication
Kuehbeck, Thomas, Hakobyan, Gor, Sikora, Axel, Chibelushi, Claude C. and Moniri, M. 2014. Evaluation of Performance Enhancement for Crash Constellation Prediction via Car-to-Car Communication. in: Communication Technologies for Vehicles Springer.
Compressive Sensing-based Target Tracking for Wireless Visual Sensor Networks
Fayed, Salema, Youssef, Sherin, El-Helw, Amr, Patwary, Mohammad and Moniri, M. 2014. Compressive Sensing-based Target Tracking for Wireless Visual Sensor Networks. in: Advances in Information Science and Applications, Volume I: Proceedings of the 18th International Conference on Computers (part of CSCC '14) Institute for Natural Sciences and Engineering (INASE).
Prediction architecture based on block matching statistics for mixed spatial-resolution multi-view video coding
Said, Hany, Moniri, M. and Chibelushi, Claude C. 2017. Prediction architecture based on block matching statistics for mixed spatial-resolution multi-view video coding. EURASIP Journal on Image and Video Processing. 2017 (1). https://doi.org/10.1186/s13640-017-0164-7
Analytical framework for Adaptive Compressive Sensing for Target Detection within Wireless Visual Sensor Networks
Fayed, Salema, Youssef, Sherin, El-Helw, Amr, Patwary, Mohammad and Moniri, M. 2017. Analytical framework for Adaptive Compressive Sensing for Target Detection within Wireless Visual Sensor Networks. Multimedia Tools and Applications. 77 (13), pp. 16533-16559. https://doi.org/10.1007/s11042-017-5227-3
A Hybrid Adaptive Compressive Sensing Model for Visual Tracking in Wireless Visual Sensor Networks
Fayed, Salema, Youssef, Sherin, El-Helw, Amr, Patwary, Mohammad and Moniri, M. 2015. A Hybrid Adaptive Compressive Sensing Model for Visual Tracking in Wireless Visual Sensor Networks. International Journal of Circuits, Systems, and Signal Processing. 9, pp. 134-144.
Adaptive compressive sensing for target tracking within wireless visual sensor networks-based surveillance applications
Fayed, Salema, M.Youssef, Sherin, El-Helw, Amr, Patwary, Mohammad and Moniri, M. 2015. Adaptive compressive sensing for target tracking within wireless visual sensor networks-based surveillance applications. Multimedia Tools and Applications. 75 (11), pp. 6347-6371. https://doi.org/10.1007/s11042-015-2575-8
Image segmentation using adaptive video analytics, Image processingUS 9047677 B2
Sedky, Mohamed Hamed Ismail, Chibelushi, Claude Chilufya and Moniri, M. 2015. Image segmentation using adaptive video analytics, Image processingUS 9047677 B2. US 13/140,378
Towards a fully automated monitoring system for Manhole Cover: Smart cities and IOT applications
Aly, Hesham H., Soliman, Abdel Hamid and Moniri, M. 2015. Towards a fully automated monitoring system for Manhole Cover: Smart cities and IOT applications. in: 2015 IEEE First International Smart Cities Conference (ISC2) IEEE. pp. 24-30