A Modified Adaboost Algorithm to Reduce False Positives in Face Detection
Joint Authors
Choi, Hyo-rim
Kim, TaeYong
Niyomugabo, Cesar
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-28
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
We present a modified Adaboost algorithm in face detection, which aims at an accurate algorithm to reduce false-positive detection rates.
We built a new Adaboost weighting system that considers the total error of weak classifiers and classification probability.
The probability was determined by computing both positive and negative classification errors for each weak classifier.
The new weighting system gives higher weights to weak classifiers with the best positive classifications, which reduces false positives during detection.
Experimental results reveal that the original Adaboost and the proposed method have comparable face detection rate performances, and the false-positive results were reduced almost four times using the proposed method.
American Psychological Association (APA)
Niyomugabo, Cesar& Choi, Hyo-rim& Kim, TaeYong. 2016. A Modified Adaboost Algorithm to Reduce False Positives in Face Detection. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-6.
https://search.emarefa.net/detail/BIM-1112301
Modern Language Association (MLA)
Niyomugabo, Cesar…[et al.]. A Modified Adaboost Algorithm to Reduce False Positives in Face Detection. Mathematical Problems in Engineering No. 2016 (2016), pp.1-6.
https://search.emarefa.net/detail/BIM-1112301
American Medical Association (AMA)
Niyomugabo, Cesar& Choi, Hyo-rim& Kim, TaeYong. A Modified Adaboost Algorithm to Reduce False Positives in Face Detection. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-6.
https://search.emarefa.net/detail/BIM-1112301
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112301