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Real-Time Feature based Face Detection and Tracking I-Cursor

by Shashank Gupta, Dhaval Dholakiya, Sunita Barve
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 48 - Number 24
Year of Publication: 2012
Authors: Shashank Gupta, Dhaval Dholakiya, Sunita Barve
10.5120/7525-7279

Shashank Gupta, Dhaval Dholakiya, Sunita Barve . Real-Time Feature based Face Detection and Tracking I-Cursor. International Journal of Computer Applications. 48, 24 ( June 2012), 1-5. DOI=10.5120/7525-7279

@article{ 10.5120/7525-7279,
author = { Shashank Gupta, Dhaval Dholakiya, Sunita Barve },
title = { Real-Time Feature based Face Detection and Tracking I-Cursor },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 48 },
number = { 24 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume48/number24/7525-7279/ },
doi = { 10.5120/7525-7279 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:44:54.444060+05:30
%A Shashank Gupta
%A Dhaval Dholakiya
%A Sunita Barve
%T Real-Time Feature based Face Detection and Tracking I-Cursor
%J International Journal of Computer Applications
%@ 0975-8887
%V 48
%N 24
%P 1-5
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This project aims to present an application that is able of replacing the traditional mouse with the human face as a new way to interact with the computer. Facial features (nose tip and eyes) are detected and tracked in real-time to use their actions as mouse events. In our work we were trying to compensate people who have hands disabilities that prevent them from using the mouse by designing an application that uses facial features (nose tip and eyes) to interact with the computer. It can be applied to a wide range of face scales. Our basic strategy for detection is fast extraction of face candidates with a Six-Segmented Rectangular (SSR) filter and face verification by a support vector machine. A motion cue is used in a simple way to avoid picking up false candidates in the background. In face tracking, the patterns of between-the eyes are tracked with updating template matching.

References
  1. P. Viola and M. Jones, "Rapid object Detection using a Boosted Cascade of Simple Features," Proc. Of IEEE Conf. CVRP,1, pp. 511-518,2001.
  2. Chiang, C. C. , Tai, W. K. , Yang, M. T. , Huang, Y. T. & Huang, C. J. , (2003). A novel method for detecting lips, eyes and faces in real-time. Real-Time Imaging 9, 277-287.
  3. Paul Viola, Michael J. Jones, "Robust Real-Time Face Detection". International Journal of Computer Vision 57(2), 137–154, 2004.
  4. Shinjiro Kawato and Nobuji Tetsutani, "Scale Adaptive Face Detection and Tracking in Real Time with SSR filter and Support Vector Machine".
  5. Oraya Sawettanusorn, Yasutaka Senda, Shinjiro Kawato, Nobuji Tetsutani, and Hironori Yamauchi, "Detection of Face Representative Using Newly Proposed Filter".
Index Terms

Computer Science
Information Sciences

Keywords

Six-segmented Rectangular (ssr) Filter

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