Real-time Hands Tracking Using Feature Point Gathering Based on KLT Tracker for Man-Machine Interface
Intuitive man-machine interfaces based on gestures with a touchpad device have become common. Furthermore, a vision based gesture recognition system like Kinect is gradually spread. Conventional works, however, use complex input devices (plural cameras, sensors, and so forth) or need to wear some devices like hand globes that is limitation for manmachine interface. This paper proposes a real-time single-input both hands tracking algorithm for intuitive man-machine interfaces. By applying feature-point gatherings into the KLT (Kanade- Lucas-Tomasi) tracker, a kind of an optical flow, non-rigid objects like hands can be traced with high accuracy and low complexity under a complex background.
Ryosuke ARAKI Takeshi IKENAGA
Waseda University, Tokyo, Japan
国际会议
2011亚太信号与信息处理协会年度峰会(APSIPAASC 2011)
西安
英文
1-1
2011-10-18(万方平台首次上网日期,不代表论文的发表时间)