Face detection architecture design using hybrid skin color detection and cascade of classifiers

Der Wei Yang; Chun Wei Chen; Che Hao Chang; Yun Chen Chang; Ming-Der Shieh; Jonas Wang; Chia Cheng Lo

doi:10.1109/APCCAS.2012.6419092

Face detection architecture design using hybrid skin color detection and cascade of classifiers

Der Wei Yang, Chun Wei Chen, Che Hao Chang, Yun Chen Chang, Ming-Der Shieh, Jonas Wang, Chia Cheng Lo

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

This paper presents an efficient face detection algorithm which results in low cost and high performance hardware implementation. Using the proposed scheme of hybrid skin color detection and cascade of classifiers, we successfully overcome (i) the poor false positive rate issue in the skin color based face detection and (ii) the huge computation complexity in the cascade of classifiers. A light variation tolerable skin color detection method and a scan-line based dynamic down-sampling architecture are also proposed to enhance the performance. Experimental results reveal that the proposed design has high detection accuracy with low hardware cost as compared with related work.

Original language	English
Title of host publication	2012 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2012
Pages	543-546
Number of pages	4
DOIs	https://doi.org/10.1109/APCCAS.2012.6419092
Publication status	Published - 2012
Event	2012 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2012 - Kaohsiung, Taiwan Duration: 2012 Dec 2 → 2012 Dec 5

Other

Other	2012 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2012
Country	Taiwan
City	Kaohsiung
Period	12-12-02 → 12-12-05

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Access to Document

10.1109/APCCAS.2012.6419092

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title = "Face detection architecture design using hybrid skin color detection and cascade of classifiers",

abstract = "This paper presents an efficient face detection algorithm which results in low cost and high performance hardware implementation. Using the proposed scheme of hybrid skin color detection and cascade of classifiers, we successfully overcome (i) the poor false positive rate issue in the skin color based face detection and (ii) the huge computation complexity in the cascade of classifiers. A light variation tolerable skin color detection method and a scan-line based dynamic down-sampling architecture are also proposed to enhance the performance. Experimental results reveal that the proposed design has high detection accuracy with low hardware cost as compared with related work.",

author = "Yang, {Der Wei} and Chen, {Chun Wei} and Chang, {Che Hao} and Chang, {Yun Chen} and Ming-Der Shieh and Jonas Wang and Lo, {Chia Cheng}",

year = "2012",

doi = "10.1109/APCCAS.2012.6419092",

language = "English",

isbn = "9781457717291",

pages = "543--546",

booktitle = "2012 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2012",

note = "2012 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2012 ; Conference date: 02-12-2012 Through 05-12-2012",

}

Yang, DW, Chen, CW, Chang, CH, Chang, YC, Shieh, M-D, Wang, J & Lo, CC 2012, Face detection architecture design using hybrid skin color detection and cascade of classifiers. in 2012 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2012., 6419092, pp. 543-546, 2012 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2012, Kaohsiung, Taiwan, 12-12-02. https://doi.org/10.1109/APCCAS.2012.6419092

Face detection architecture design using hybrid skin color detection and cascade of classifiers. / Yang, Der Wei; Chen, Chun Wei; Chang, Che Hao; Chang, Yun Chen; Shieh, Ming-Der; Wang, Jonas; Lo, Chia Cheng.

2012 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2012. 2012. p. 543-546 6419092.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - This paper presents an efficient face detection algorithm which results in low cost and high performance hardware implementation. Using the proposed scheme of hybrid skin color detection and cascade of classifiers, we successfully overcome (i) the poor false positive rate issue in the skin color based face detection and (ii) the huge computation complexity in the cascade of classifiers. A light variation tolerable skin color detection method and a scan-line based dynamic down-sampling architecture are also proposed to enhance the performance. Experimental results reveal that the proposed design has high detection accuracy with low hardware cost as compared with related work.

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