Real time face detection system based edge restoration and nested K-means at frontal view

Paper


Joo, Hyun Jea, Jang, Bong Won, Bashar, Md. Rezaul and Rhee, Phill Kyu. 2006. "Real time face detection system based edge restoration and nested K-means at frontal view." Wang, Lipo (ed.) 3rd International Conference on Fuzzy Systems and Knowledge Discovery . Xi'an, China 24 - 28 Sep 2006 Berlin / Heidelberg, Germany. https://doi.org/10.1007/11881599_148
Paper/Presentation Title

Real time face detection system based edge restoration and nested K-means at frontal view

Presentation TypePaper
AuthorsJoo, Hyun Jea (Author), Jang, Bong Won (Author), Bashar, Md. Rezaul (Author) and Rhee, Phill Kyu (Author)
EditorsWang, Lipo
Journal or Proceedings TitleLecture Notes in Artificial Intelligence (Book series)
ERA Conference ID43362
Journal Citation4223, pp. 1192-1200
Number of Pages9
Year2006
Place of PublicationBerlin / Heidelberg, Germany
ISBN9783540459163
Digital Object Identifier (DOI)https://doi.org/10.1007/11881599_148
Web Address (URL) of Paperhttps://link.springer.com/chapter/10.1007%2F11881599_148
Conference/Event3rd International Conference on Fuzzy Systems and Knowledge Discovery
International Conference on Fuzzy Systems and Knowledge
Event Details
International Conference on Fuzzy Systems and Knowledge
FSKD
Rank
C
C
C
Event Details
3rd International Conference on Fuzzy Systems and Knowledge Discovery
Event Date
24 to end of 28 Sep 2006
Event Location
Xi'an, China
Abstract

Bayesian technique is a popular tool for object detection due to its high efficiency. As it compares pixel by pixel, it takes a lot of execution time. This paper addresses a novel framework for head detection with minimum time and high accuracy. To detect head from motion pictures, motion segmentation algorithm is employed.
The novelty of this paper carried out with the following steps: frame differencing, preprocessing, detecting edge lines and restoration, finding the head area and cutting the head candidate. Moreover, nested K-means algorithm is adopted to find head location and statistical modeling is employed to determine face or non-face class, while Bayesian Discriminating Features (BDF) method is employed to verify the faces. Finally, the proposed system is carried out with a lot of experiments and a recognizable success is notified

Keywordsedge detection; face recognition; image segmentation; motion pictures; object recognition; statistical methods; Bayesian technique; motion segmentation algorithms; object detection; real time face detection systems
ANZSRC Field of Research 2020469999. Other information and computing sciences not elsewhere classified
460306. Image processing
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Byline AffiliationsInha University, Korea
SeriesLecture Notes in Artificial Intelligence
Book TitleFuzzy Systems and Knowledge Discovery
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