Volume & Issue no: Volume 4, Issue 6, November - December 2015
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Title: |
Enhanced Face Detection and Tracking In Video
Sequence Using Fuzzy Face Model and Sparse
Representation Technique |
Author Name: |
Manjunatha Hiremath, P. S. Hiremath |
Abstract: |
Abstract
The human face detection from video sequences is an
important biometric component in the design of intelligent
human computer interaction systems for video surveillance,
face recognition, emotion recognition and face database
management. In this paper, an automatic and robust method
to detect human faces from video sequences and track the
same is proposed. A novel algorithm for segmentation of face
regions in video images based on fuzzy geometric face model
is developed. The sparse representation algorithm is used to
track the face along the video sequence. The proposed method,
which is developed as a simple face detection and tracking
approach, is implemented and evaluated with numerous
experiments on videos containing large variations of head
motion, light condition, and facial expressions. The
experimental results show that the proposed method is
effective in detecting and tracking human faces in videos.
Keywords: Face detection, Segmentation, Fuzzy
geometric face model. |
Cite this article: |
Manjunatha Hiremath, P. S. Hiremath , "
Enhanced Face Detection and Tracking In Video
Sequence Using Fuzzy Face Model and Sparse
Representation Technique" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) ,
Volume 4, Issue 6, November - December 2015 , pp.
099-104 , ISSN 2278-6856.
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