A Novel Preprocessing Technique for Training Viola-Jones Hand Detector

Material type: 文書・図像類

Author: ブ, シュクケイほか

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Publication date: 2014-06

Material Format: Paper

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Note (General)：: Viola-Jones method combines Haar-like features with AdaBoost classifier. It is widely used in real time object detection due to its high performance a...

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Paper

Material Type: 文書・図像類
Title: A Novel Preprocessing Technique for Training Viola-Jones Hand Detector
Author/Editor: ブ, シュクケイ
Bu, Shukukei
長橋, 宏
NAGAHASHI, HIROSHI
Author Heading: ブ, シュクケイ
Bu, Shukukei
長橋, 宏
NAGAHASHI, HIROSHI
Publication Date: 2014-06
Publication Date (W3CDTF): 2014-06
Periodical title: IEICE Technical Report
No. or year of volume/issue: 114 no. 90
Volume: 114
Issue: no. 90
Pages: 37-41
Text Language Code: eng
Target Audience: 一般
Note (General): Viola-Jones method combines Haar-like features with AdaBoost classifier. It is widely used in real time object detection due to its high performance and rapidity. Viola-Jones method has achieved considerable success in face detection. However, when it is applied to hand detection, the false positive rate is rather high. Compared with face training samples which contain little background area, hand training samples include diverse backgrounds. Therefore it is substantially difficult to find common hand features in the training of hand detectors. To solve this problem, we propose a novel preprocessing technique which can reduce the bad influence of backgrounds included in hand training samples. Experimental results show that our method needs far less training samples than Viola-Jones method and improves the false positive rate significantly.
identifier:oai:t2r2.star.titech.ac.jp:50279289
Data Provider (Database): 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）
https://irdb.nii.ac.jp
Original Data Provider (Database): 東京工業大学 : 東京工業大学リサーチリポジトリ