Mixture models with skin and shadow probabilities for fingertip input applications

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/107035

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/107035

Title:	Mixture models with skin and shadow probabilities for fingertip input applications
Authors:	鄭旭詠;Yu, Chih-Chang;Cheng, Hsu-Yung;Lee, Chien-Cheng
Contributors:	資訊電機學院資訊工程學系
Keywords:	Applied sciences;Artificial intelligence;Computer science;control theory;systems;Computer systems and distributed systems. User interface;Data processing. List processing. Character string processing;Exact sciences and technology;Feature extraction;Gaussian;Human–computer interface;Mandarin phonetic symbol;Memory organisation. Data processing;Mixture models;Moving skin region detection;Pattern recognition. Digital image processing. Computational geometry;Shadow detection;Software;Speech and sound recognition and synthesis. Linguistics;Video-based fingertip input;Virtual touch keyboard
Date:	2013-06-28
Issue Date:	2026-04-23 13:53:52 (UTC+8)
Publisher:	Academic Press Inc.;Amsterdam: Elsevier Inc
Abstract:	摘要： •Moving skin regions and shadows are detected.•Skin and shadow probabilities are integrated into the mixture models.•Learning rates are adjusted by the skin and shadow probabilities.•Mandarin Phonetic Symbol (MPS) combination recognition algorithm is designed.•Single fingertip virtual keyboard system is implemented. This paper proposes an accurate moving skin region detection method for video-based human–computer interface using gestures or fingertips. Using Gaussian mixture models as groundwork, the proposed method expresses the features of skins in a probability form and incorporates them into the mixture-based framework. Moreover, to alleviate the influence of shadows, the properties of shadows are also formulated as probabilities and used for shadow detection and elimination. In addition to moving skin region detection, this paper also develops two practical fingertip input applications to demonstrate the accuracy of the proposed detection method. The two applications are Mandarin Phonetic Symbol combination recognition system and single fingertip virtual keyboard implementation. Experimental results have shown the advantages of the proposed detection method and the effectiveness of the two application implementations. 出版者： Amsterdam: Elsevier Inc 出版日期： 2013-10-01 出處： Journal of visual communication and image representation, 2013-10, Vol.24 (7), p.819-828 資源來源： ScienceDirect (Elsevier) Journals 版權： 2013 Elsevier Inc. 版權： 2014 INIST-CNRS 識別號： ISSN: 1047-3203 識別號： EISSN: 1095-9076 識別號： DOI: 10.1016/j.jvcir.2013.05.009
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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