Pattern recognition using graph signal processing for large-scale time-sequence data

Research Project

Project/Area Number	15K12061
Research Category	Grant-in-Aid for Challenging Exploratory Research
Allocation Type	Multi-year Fund
Research Field	Perceptual information processing
Research Institution	Tokyo Institute of Technology
Principal Investigator	Koichi Shinoda 東京工業大学, 情報理工学院, 教授 (10343097)
Co-Investigator(Kenkyū-buntansha)	井上中順東京工業大学, 情報理工学院, 助教 (10733397)
Project Period (FY)	2015-04-01 – 2018-03-31
Project Status	Completed (Fiscal Year 2017)
Budget Amount *help	¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000) Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000) Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000) Fiscal Year 2015: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Keywords	動作認識 / グラフ信号処理 / 深度カメラ / 音声認識 / 映像認識
Outline of Final Research Achievements	We have developed an action recognition method from RGB-D camera inputs. This method uses a time sequence of human skeleton as an input. Every frame it extracts features by using spectral graph wavelet transform. Then the features are pooled in a hierarchical way in the time axis. This method achieved the state-of-the-art in multi-view action recognition.

Report

(4 results)