Detecting occluded faces in unconstrained crowd digital pictures

S. Janahiram; Abeer Alsadoon; P. W. C. Prasad; A. M. S. Rahma; A. Elchouemi; S. M. N. Arosha Senanayake

doi:10.1109/ICMIP.2016.11

Detecting occluded faces in unconstrained crowd digital pictures

S. Janahiram , Abeer Alsadoon, P. W. C. Prasad, A. M. S. Rahma, A. Elchouemi, S. M. N. Arosha Senanayake

Research output: Book chapter/Published conference paper › Conference paper › peer-review

1 Citation (Scopus)

Abstract

Face detection and recognition mechanisms are widely used in many multimedia and security devices. The concept is called face detection and there are significant numbers of studies into face recognition, particularly for image processing and computer vision. However, there remain significant challenges in the existing systems due to limitations behind algorithms. Viola Jones and Cascade Classifier are considered the best algorithms from among existing systems. They can detect faces in unconstrained Crowd Scene with half and full face detection methods. However, limitations of these systems are affecting accuracy and processing time. This project presents a propose solution called VJaC (Viola Jones and Cascade). It is based on the study of current systems, features and limitations. This system considered three main factors, processing time, accuracy and training. These factors are tested on different sample images, and compared with current systems.

Original language	English
Title of host publication	Proceedings of 2016 1st International conference on multimedia and image processing ICMIP 2016
Place of Publication	United States
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	5-9
Number of pages	5
ISBN (Electronic)	9781467389402
ISBN (Print)	9781467389419
DOIs	https://doi.org/10.1109/ICMIP.2016.11
Publication status	Published - 21 Sept 2016
Event	1st International Conference on Multimedia and Image Processing: ICMIP 2016 - University of Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam Duration: 01 Jun 2016 → 03 Jun 2016 http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7573054 (Preface to Proceedings)

Conference

Conference	1st International Conference on Multimedia and Image Processing
Country/Territory	Brunei Darussalam
City	Bandar Seri Begawan
Period	01/06/16 → 03/06/16
Internet address	http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7573054 (Preface to Proceedings)

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10.1109/ICMIP.2016.11

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Janahiram , S., Alsadoon, A., Prasad, P. W. C., Rahma, A. M. S., Elchouemi, A., & Senanayake, S. M. N. A. (2016). Detecting occluded faces in unconstrained crowd digital pictures. In Proceedings of 2016 1st International conference on multimedia and image processing ICMIP 2016 (pp. 5-9). Article 7573058 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICMIP.2016.11

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title = "Detecting occluded faces in unconstrained crowd digital pictures",

abstract = "Face detection and recognition mechanisms are widely used in many multimedia and security devices. The concept is called face detection and there are significant numbers of studies into face recognition, particularly for image processing and computer vision. However, there remain significant challenges in the existing systems due to limitations behind algorithms. Viola Jones and Cascade Classifier are considered the best algorithms from among existing systems. They can detect faces in unconstrained Crowd Scene with half and full face detection methods. However, limitations of these systems are affecting accuracy and processing time. This project presents a propose solution called VJaC (Viola Jones and Cascade). It is based on the study of current systems, features and limitations. This system considered three main factors, processing time, accuracy and training. These factors are tested on different sample images, and compared with current systems.",

keywords = "Face detection, Face recognition, Unconstrained crowd digital pictures",

author = "S. Janahiram and Abeer Alsadoon and Prasad, {P. W. C.} and Rahma, {A. M. S.} and A. Elchouemi and Senanayake, {S. M. N. Arosha}",

note = "Includes bibliographical references.; 1st International Conference on Multimedia and Image Processing : ICMIP 2016 ; Conference date: 01-06-2016 Through 03-06-2016",

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doi = "10.1109/ICMIP.2016.11",

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booktitle = "Proceedings of 2016 1st International conference on multimedia and image processing ICMIP 2016",

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Janahiram , S, Alsadoon, A, Prasad, PWC, Rahma, AMS, Elchouemi, A & Senanayake, SMNA 2016, Detecting occluded faces in unconstrained crowd digital pictures. in Proceedings of 2016 1st International conference on multimedia and image processing ICMIP 2016., 7573058, IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 5-9, 1st International Conference on Multimedia and Image Processing, Bandar Seri Begawan, Brunei Darussalam, 01/06/16. https://doi.org/10.1109/ICMIP.2016.11

Detecting occluded faces in unconstrained crowd digital pictures. / Janahiram , S.; Alsadoon, Abeer; Prasad, P. W. C. et al.
Proceedings of 2016 1st International conference on multimedia and image processing ICMIP 2016. United States: IEEE, Institute of Electrical and Electronics Engineers, 2016. p. 5-9 7573058.

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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AU - Janahiram , S.

AU - Alsadoon, Abeer

AU - Prasad, P. W. C.

AU - Rahma, A. M. S.

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N2 - Face detection and recognition mechanisms are widely used in many multimedia and security devices. The concept is called face detection and there are significant numbers of studies into face recognition, particularly for image processing and computer vision. However, there remain significant challenges in the existing systems due to limitations behind algorithms. Viola Jones and Cascade Classifier are considered the best algorithms from among existing systems. They can detect faces in unconstrained Crowd Scene with half and full face detection methods. However, limitations of these systems are affecting accuracy and processing time. This project presents a propose solution called VJaC (Viola Jones and Cascade). It is based on the study of current systems, features and limitations. This system considered three main factors, processing time, accuracy and training. These factors are tested on different sample images, and compared with current systems.

AB - Face detection and recognition mechanisms are widely used in many multimedia and security devices. The concept is called face detection and there are significant numbers of studies into face recognition, particularly for image processing and computer vision. However, there remain significant challenges in the existing systems due to limitations behind algorithms. Viola Jones and Cascade Classifier are considered the best algorithms from among existing systems. They can detect faces in unconstrained Crowd Scene with half and full face detection methods. However, limitations of these systems are affecting accuracy and processing time. This project presents a propose solution called VJaC (Viola Jones and Cascade). It is based on the study of current systems, features and limitations. This system considered three main factors, processing time, accuracy and training. These factors are tested on different sample images, and compared with current systems.

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Detecting occluded faces in unconstrained crowd digital pictures

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