講演名 2014-03-14
Study of Recognizing Hand Actions from Video Sequences during Suture Surgeries Based on Temporally-Sectioned SIFT and Sliding Window Based Neural Networks
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抄録(和)
抄録(英) Towards the realization of a robotic nurse that can support surgeries autonomously by recognizing surgical situations only using video informations, this paper proposes an improved method by using sectioned-SIFT and sliding window based neural network that can recognize surgeon's hand actions: suture and tying. Hand area is detected by using color information and then the video sequence is partitioned into sections. Sectioned-SIFT descriptors are computed in each section and built a word vocabulary. Histogram feature of the action is spliced by using word's frequency in each section. Finally, sliding window and neural network is used to recognize the significant actions: suture and tying. The proposed method has achieved the 100% recognition rate for manually extracted actions and 90% recognition rate for whole surgery video sequences.
キーワード(和)
キーワード(英) action recognition / sectioned-SIFT / BP neural network / RSN
資料番号 PRMU2013-193
発行日

研究会情報
研究会 PRMU
開催期間 2014/3/6(から1日開催)
開催地(和)
開催地(英)
テーマ(和)
テーマ(英)
委員長氏名(和)
委員長氏名(英)
副委員長氏名(和)
副委員長氏名(英)
幹事氏名(和)
幹事氏名(英)
幹事補佐氏名(和)
幹事補佐氏名(英)

講演論文情報詳細
申込み研究会 Pattern Recognition and Media Understanding (PRMU)
本文の言語 ENG
タイトル(和)
サブタイトル(和)
タイトル(英) Study of Recognizing Hand Actions from Video Sequences during Suture Surgeries Based on Temporally-Sectioned SIFT and Sliding Window Based Neural Networks
サブタイトル(和)
キーワード(1)(和/英) / action recognition
第 1 著者 氏名(和/英) / Ye Li
第 1 著者 所属(和/英)
Graduate School of Global Information and Telecommunication Studies, Waseda University
発表年月日 2014-03-14
資料番号 PRMU2013-193
巻番号(vol) vol.113
号番号(no) 493
ページ範囲 pp.-
ページ数 6
発行日