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

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.