Face Region Detection on Skin Chrominance from Color Images by Facial Features

2004 ◽  
pp. 646-646
Author(s):  
Jin Ok Kim ◽  
Jin Soo Kim ◽  
Chin Hyun Chung
Keyword(s):  
Color Images ◽  
Facial Features ◽  
Region Detection ◽  
Face Region

Color Images Illumination Compensation Method for Human Face Region Detection

2014 ◽  
Vol 678 ◽  
pp. 162-165 ◽  
Author(s):  
Yang Yu ◽  
Xiao Bin Li ◽  
Hai Yan Sun
Keyword(s):  
Color Images ◽  
Compensation Method ◽  
Detection Accuracy ◽  
Human Face ◽  
Light Conditions ◽  
Illumination Compensation ◽  
Facial Region ◽  
Region Detection ◽  
Face Region ◽  
California Institute Of Technology

Facial region detection has broad application prospects, but existing human face region detection methods have some rigorous requirements for the light conditions. Error detection about face area caused by the poor light conditions has a great bad effect on the follow-up processing, such as face recognition, fatigue degree evaluation based on visual. So face region detection in complex lighting conditions has always been the difficult problem. Therefore a self-adaptive illumination compensation method for color images has been proposed. Select the color face images database of the California Institute of Technology to test the method dealing with the face region detection by original image and the image after illumination compensation. In the simulation experiment, the method of Illumination compensation can effectively improve the detection accuracy. Lay the foundation for driver fatigue detection based on visual.

Human Face Region Detection Driving Activity Recognition in Video

2018 ◽  
pp. 2102-2123
Author(s):  
Anastasios Doulamis ◽  
Athanasios Voulodimos ◽  
Theodora Varvarigou
Keyword(s):  
Activity Recognition ◽  
Human Face ◽  
Multiple Streams ◽  
Body Movements ◽  
Video Signals ◽  
Region Detection ◽  
Face Region ◽  
Classification Framework ◽  
Fusion Methods ◽  
Tremendous Impact

Automatic recognition of human actions from video signals is probably one of the most salient research topics of computer vision with a tremendous impact for many applications. In this chapter, the authors introduce a new descriptor, the Human Constrained Pixel Change History (HC-PCH), which is based on PCH but focuses on the human body movements over time. They propose a modification of the conventional PCH that entails the calculation of two probabilistic maps based on human face and body detection, respectively. These HC-PCH features are used as input to an HMM-based classification framework, which exploits redundant information from multiple streams by employing sophisticated fusion methods, resulting in enhanced activity recognition rates.

Adaptive compressed sensing of color images based on salient region detection

2019 ◽  
Vol 79 (21-22) ◽  
pp. 14777-14791
Author(s):  
Zheng Zhang ◽  
Hongbo Bi ◽  
Xiaoxue Kong ◽  
Ning Li ◽  
Di Lu
Keyword(s):  
Compressed Sensing ◽  
Color Images ◽  
Salient Region Detection ◽  
Salient Region ◽  
Region Detection

Human Face Region Detection Driving Activity Recognition in Video

2014 ◽  
pp. 316-335
Author(s):  
Anastasios Doulamis ◽  
Athanasios Voulodimos ◽  
Theodora Varvarigou
Keyword(s):  
Activity Recognition ◽  
Human Face ◽  
Multiple Streams ◽  
Body Movements ◽  
Video Signals ◽  
Region Detection ◽  
Face Region ◽  
Classification Framework ◽  
Fusion Methods ◽  
Tremendous Impact

Automatic recognition of human actions from video signals is probably one of the most salient research topics of computer vision with a tremendous impact for many applications. In this chapter, the authors introduce a new descriptor, the Human Constrained Pixel Change History (HC-PCH), which is based on PCH but focuses on the human body movements over time. They propose a modification of the conventional PCH that entails the calculation of two probabilistic maps based on human face and body detection, respectively. These HC-PCH features are used as input to an HMM-based classification framework, which exploits redundant information from multiple streams by employing sophisticated fusion methods, resulting in enhanced activity recognition rates.

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