Human face detection in digital video using SVM ensemble
SCIE
SCOPUS
- Title
- Human face detection in digital video using SVM ensemble
- Authors
- Je, HM; Kim, D; Bang, SY
- Date Issued
- 2003-06
- Publisher
- KLUWER ACADEMIC PUBL
- Abstract
- This Letter proposes automatic human face detection in digital video using a support vector machine (SVM) ensemble to improve the detection performance. The SVM ensemble consists of several independently trained SVMs using randomly chosen training samples via a bootstrap technique. Next, they are aggregated in order to make a collective decision via a majority voting scheme. Experimental results show that the proposed face detection method using SVM ensemble outperforms conventional methods such as using only single SVM and Multi-Layer Perceptron in terms of classification accuracy, false alarms, and missing rates.
- Keywords
- face detection; majority voting; support vector machine; support vector machine ensemble; SUPPORT VECTOR MACHINES
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/18303
- DOI
- 10.1023/A:1026097128675
- ISSN
- 1370-4621
- Article Type
- Article
- Citation
- NEURAL PROCESSING LETTERS, vol. 17, no. 3, page. 239 - 252, 2003-06
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- There are no files associated with this item.
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