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Tracking of nose tip: An alternative for mouse

Publication Type : Journal Article

Thematic Areas : TIFAC-CORE in Cyber Security

Publisher : Lecture Notes in Computer Science

Source : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 6411 LNCS, Tiruchirappalli, p.219-225 (2012)

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-84858011349&partnerID=40&md5=8c12fc5594889e105fb71cfb23c36e31

ISBN : 9783642278716

Keywords : Ambient environment, Computational paradigm, Device control, Gesture recognition, Human gestures, Human wits, Mammals, Phase A, Real world domain, Reference points, Single cameras, Tracking (position)

Campus : Coimbatore

School : Centre for Cybersecurity Systems and Networks, School of Engineering

Center : TIFAC CORE in Cyber Security

Department : Computer Science, cyber Security

Verified : Yes

Year : 2012

Abstract : Gesture recognition is mainly apprehensive on analyzing the functionality of human wits. The primary goal of gesture recognition research is to create a system which can recognize specific human gestures and use them to convey information or for device control. The purpose of this paper is to interface machines directly to human wits without any corporeal media in an ambient environment. This work pertains to reckoning on tracking of nose tip. In the pragmatic phenomenon the nose tip is tracked and mouse positioning event is generated on how the nose tip moves on the real world domain. In effectuation phase a single camera based computational paradigm is used for tracking nose tip, and recognizing gestures. Reference point location tracking method is used to spot nose tip in successive frames. © 2012 Springer-Verlag.

Cite this Research Publication : Dr. Gireesh K. T., Poornaselvan, K. Jb, ,, ,, and Sreevathsan, Ra, “Tracking of nose tip: An alternative for mouse”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6411 LNCS, pp. 219-225, 2012.

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