TY - GEN
T1 - Intelligent human detection based on depth information
AU - Chen, Tzu Wei
AU - Lin, Ku Ying
AU - Chen, Yon Ping
N1 - Publisher Copyright:
© 2013; MVA Organization. All rights reserved.
PY - 2013
Y1 - 2013
N2 - This paper proposes an intelligent human detection system based on the depth information generated by Kinect to find out humans from a sequence of images and resolve occlusion problems. The system is divided into three parts, including region-of-interest (ROI) selection, feature extraction and human recognition. First, the histogram projection and connected component labeling are applied to select the ROIs according to the property that human would present vertically in general. Then, normalize the ROIs based on the distances between objects and camera and extract the human shape feature by the edge detection and distance transformation to obtain the distance image. Finally, the chamfer matching is used to search possible parts of the human body under component-based concept, and then shape recognition is implemented according to the combination ofparts of the human body. From the experimental results, the system could detect humans with high-accuracy rate and resolve occlusion problems.
AB - This paper proposes an intelligent human detection system based on the depth information generated by Kinect to find out humans from a sequence of images and resolve occlusion problems. The system is divided into three parts, including region-of-interest (ROI) selection, feature extraction and human recognition. First, the histogram projection and connected component labeling are applied to select the ROIs according to the property that human would present vertically in general. Then, normalize the ROIs based on the distances between objects and camera and extract the human shape feature by the edge detection and distance transformation to obtain the distance image. Finally, the chamfer matching is used to search possible parts of the human body under component-based concept, and then shape recognition is implemented according to the combination ofparts of the human body. From the experimental results, the system could detect humans with high-accuracy rate and resolve occlusion problems.
UR - http://www.scopus.com/inward/record.url?scp=85083082624&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85083082624
SN - 9784901122139
T3 - Proceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013
SP - 286
EP - 289
BT - Proceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013
PB - MVA Organization
T2 - 13th IAPR International Conference on Machine Vision Applications, MVA 2013
Y2 - 20 May 2013 through 23 May 2013
ER -