Prominent Boundaries and Foreground Detection Based Technique for Human Face Extraction from Color Images Containing Complex Background

2011 ◽  
Author(s):  
Darshak G. Thakore ◽  
A.I. Trivedi
Keyword(s):  
Color Images ◽  
Foreground Detection ◽  
Human Face ◽  
Complex Background

scholarly journals Human Face Detection in Color Images

2021 ◽  
Author(s):  
Jun Gao
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Video Retrieval ◽  
Color Images ◽  
Human Face ◽  
Detection Scheme ◽  
Retrieval Systems ◽  
Human Face Detection ◽  
The Face ◽  
Video Retrieval Systems

Detection of human face has many realistic and important applications such as human and computer interface, face recognition, face image database management, security access control systems and content-based indexing video retrieval systems. In this report a face detection scheme will be presented. The scheme is designed to operate on color images. In the first stage of algorithm, the skin color regions are detected based on the chrominance information. A color segmentation stage is then employed to make skin color regions to be divided into smaller regions which have homogenous color. Then, we use the iterative luminance segmentation to further separate the detected skin region from other skin-colored objects such as hair, clothes, and wood, based on the high variance of the luminance component in the neighborhood of edges of objects. Post-processing is applied to determine whether skin color regions fit the face constrains on density of skin, size, shape and symmetry and contain the facial features such as eyes and mouths. Experimental results show that the algorithm is robust and is capable of detecting multiple faces in the presence of a complex background which contains the color similar to the skin tone.

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.

Automatic human face location in a complex background using motion and color information

1996 ◽  
Vol 29 (11) ◽  
pp. 1877-1889 ◽  
Author(s):  
Choong Hwan LEE ◽  
Jun Sung Kim ◽  
Kyu Ho Park
Keyword(s):  
Human Face ◽  
Color Information ◽  
Complex Background ◽  
Face Location

scholarly journals Complex background model and foreground detection based on random aggregation

2015 ◽  
Vol 64 (15) ◽  
pp. 150701
Author(s):  
Bi Guo-Ling ◽  
Xu Zhi-Jun ◽  
Chen Tao ◽  
Wang Jian-Li ◽  
Zhang Yan-Kun
Keyword(s):  
Background Model ◽  
Foreground Detection ◽  
Complex Background ◽  
Random Aggregation

scholarly journals Skin Detection and Segmentation of Human Face in Color Images

2011 ◽  
Vol 4 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Baozhu Wang ◽  
◽  
Xiuying Chang ◽  
Cuixiang Liu ◽  
◽  
...  
Keyword(s):  
Color Images ◽  
Skin Detection ◽  
Human Face

Human Motion Tracking and Alarm System Based on DaVinci

2014 ◽  
Vol 568-570 ◽  
pp. 647-651
Author(s):  
Yuan Yi Xiong ◽  
Jie Yang ◽  
Chuan Wang
Keyword(s):  
Motion Tracking ◽  
Warning System ◽  
Human Motion ◽  
Foreground Detection ◽  
Alarm System ◽  
Human Motion Tracking ◽  
Complex Background ◽  
Camshift Algorithm

The paper proposes a improved Camshift algorithm which solve the problem of the original Camshift that have limitations when the tracking target have similar color with the background and is obstructed. The paper combines codebook model with the Camshift. The YUV space is used in foreground detection rather than the RGB. The results of experiments show that the algorithm works well in complex background, occlusion and the same color interference. At last we achieve a warning system.

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