Multi-Person Pose Estimation Using a Zigbee Sensor Network

• Main Authors: Chun-Wei Chen, 陳俊瑋
• Other Authors: Kai-Tai Song
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/85411438899345322818

碩士 === 國立交通大學 === 電機與控制工程系所 === 95 === In this thesis, a multi-person pose recognition system has been developed. This system includes a human pose detection module, a CC2420DBK board and a multi-person pose monitoring software module. The human pose detection module consists of a triaxial accelerometer, a Zigbee chip and an 8-bit microcontroller. Several human pose detection modules and the CC2420DBK board form a Zigbee wireless network. The CC2420DBK board works as the receiver of the Zigbee wireless sensor network and communicates with the robot onboard computer through RS-232 link. The multi-person pose monitoring software monitors and records activities of multiple users simultaneously. We propose a pose classification algorithm by combining time-domain analysis and wavelet transform analysis. This algorithm has been implemented in the microcontroller of the human pose estimation module. Through the algorithm, the system can classify seven human poses: falling, standing, sitting, lying, walking, going upstairs and going downstairs. A pose recognition rate of 88% has been demonstrated after testing the system by five different users.