scholarly journals Human Body Segmentation Using Level Set-Based Active Contours With Application on Activity Recognition

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 157841-157858
Author(s):  
Madallah Alruwaili ◽  
Muhammad Hameed Siddiqi ◽  
Amjad Ali
Keyword(s):  
Activity Recognition ◽  
Level Set ◽  
Human Body ◽  
Active Contours ◽  
Body Segmentation ◽  
Human Body Segmentation

Human Body Segmentation Based on Shape Model and Level Set

2013 ◽  
Vol 433-435 ◽  
pp. 261-266
Author(s):  
Ying Na Deng ◽  
Xue Mei Hou
Keyword(s):  
Level Set ◽  
Human Body ◽  
Initial Contour ◽  
Model Matching ◽  
Shape Model ◽  
Shape Models ◽  
Human Object ◽  
Body Segmentation ◽  
Human Body Segmentation ◽  
Tracking And Recognition

Human body segmentation is important for object tracking and recognition. When there are multiple human bodies, because of inter-occlusion, human body precise segmentation is difficult. A segmentation method based on prior shape model and level set is proposed. Human coarse shape models are constructed with position, scale and posture. For each human body, its corresponding human shape model is obtained by model matching by which position is obtained roughly after model matching, and object precise contour is obtained through curve evolution by multiphase level set with initial contour obtained from shape model. The proposed method could segment human object precisely.

scholarly journals Graph Cut-Based Human Body Segmentation in Color Images Using Skeleton Information from the Depth Sensor

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 393 ◽  
Author(s):  
Jonha Lee ◽  
Dong-Wook Kim ◽  
Chee Won ◽  
Seung-Won Jung
Keyword(s):  
Human Body ◽  
Color Image ◽  
Depth Image ◽  
Body Region ◽  
Reasonable Accuracy ◽  
Depth Sensor ◽  
Complicated Shape ◽  
Depth Sensors ◽  
Body Segmentation ◽  
Human Body Segmentation

Segmentation of human bodies in images is useful for a variety of applications, including background substitution, human activity recognition, security, and video surveillance applications. However, human body segmentation has been a challenging problem, due to the complicated shape and motion of a non-rigid human body. Meanwhile, depth sensors with advanced pattern recognition algorithms provide human body skeletons in real time with reasonable accuracy. In this study, we propose an algorithm that projects the human body skeleton from a depth image to a color image, where the human body region is segmented in the color image by using the projected skeleton as a segmentation cue. Experimental results using the Kinect sensor demonstrate that the proposed method provides high quality segmentation results and outperforms the conventional methods.

Robust human body segmentation based on part appearance and spatial constraint

2013 ◽  
Vol 118 ◽  
pp. 191-202 ◽  
Author(s):  
Lei Huang ◽  
Sheng Tang ◽  
Yongdong Zhang ◽  
Shiguo Lian ◽  
Shouxun Lin
Keyword(s):  
Human Body ◽  
Spatial Constraint ◽  
Body Segmentation ◽  
Human Body Segmentation
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