Reducing False Positive Rate for Viola-Jones Method in Hand Detection

• 資料種別: 文書・図像類
• タイトル: Reducing False Positive Rate for Viola-Jones Method in Hand Detection
• 著者・編者: ブ, シュクケイ; Bu, Shukukei; 長橋, 宏; NAGAHASHI, HIROSHI
• 著者標目: ブ, シュクケイ; Bu, Shukukei; 長橋, 宏; NAGAHASHI, HIROSHI
• 出版年月日等: 2013-09
• 出版年（W3CDTF）: 2013-09
• タイトル（掲載誌）: Technical Report of Technical Committee on Pattern Recognition
• 巻号年月日等（掲載誌）: 113 no. 196
• 掲載巻: 113
• 掲載号: no. 196
• 掲載ページ: 149-153
• 本文の言語コード: eng
• 対象利用者: 一般
• 一般注記: The Viola-Jones object detector is a machine learning based method which combines Haar-like features with AdaBoost classifier. It is known that this method is the mainstream in face detections due to its high performance of both detection speed and precision. However, the false positive rate increases dramatically when this approach is applied to detect hands in a sign language video which includes other skin color parts such as faces or arms. In this paper, we analyze the reason for mis-detecting of these points and propose a new method to reduce the false positive rate. Experimental results have shown that our method is more robust to hand motion and decreases the false positive rate significantly.; identifier:oai:t2r2.star.titech.ac.jp:50279297
• 連携機関・データベース: 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
• 提供元機関・データベース: 東京工業大学 : 東京工業大学リサーチリポジトリ