Face detection for video summary using illumination-compensation and morphological processing

Authors:
Jae-Ung Yun;Hyung-Jin Lee;Anjan Kumar Paul;Joong-Hwan Baek
Affiliations:
Department of Information and Telecommunications Engineering, Korea Aerospace University, 200-1 Hwajun-dong, Goyang, Republic of Korea;Department of Information and Telecommunications Engineering, Korea Aerospace University, 200-1 Hwajun-dong, Goyang, Republic of Korea;Department of Information and Telecommunications Engineering, Korea Aerospace University, 200-1 Hwajun-dong, Goyang, Republic of Korea;Department of Information and Telecommunications Engineering, Korea Aerospace University, 200-1 Hwajun-dong, Goyang, Republic of Korea
Venue:
Pattern Recognition Letters
Year:
2009

Citing 5
Cited 1

Example-Based Learning for View-Based Human Face Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparative Performance of Different Skin Chrominance Models and Chrominance Spaces for the Automatic Detection of Human Faces in Color Images

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Comparative Performance of Different Skin Chrominance Models and Chrominance Spaces for the Automatic Detection of Human Faces in Color Images

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Face detection using one-class-based support vectors

FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Content-based movie analysis and indexing based on audiovisual cues

IEEE Transactions on Circuits and Systems for Video Technology

Detection and tracking faces in unconstrained color video streams

ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II

Quantified Score

Hi-index	0.10

Visualization

Abstract

This paper presents a simple and robust face detection algorithm that can be utilized to video summary. Because the characteristic of the face can be changed from unexpected condition like as shadows or lighting, we firstly process the illumination-compensation for maintaining face components. We then analyze color-based face region in YCbCr space to obtain the skin color. Also, we apply the morphological processing to improve the detection performance and reducing the number of false detected face regions. This process finds the candidates in face region and removes noise from the non-face region. For localization of the face region, we make a proper face ratio based on golden ratio. We evaluate our algorithm in the various genres. Experimental results demonstrate the effectiveness of our face detection algorithm that leads 96.7% in precision ratio on the average. The proposed method is applicable to video summary because of these high performances with low complexity.