FACE DETECTION FOR VIDEO SUMMARY USING ENHANCEMENT BASED FUSION STRATEGY

Abstract

This paper investigates a fusion strategy in the enhancement-based skin color segmentation approach that can improve the performance of face detection algorithm. The algorithm is invariant for the complex background, skin races, indoor and outdoor lighting conditions. The algorithm is split into three phases. The first phase adopts spatial transform techniques in parallel to improve the contrast of the image, transform the enhanced images into YCbCr images, apply skin segmentation technique and yield the binary segmented images. The second phase calculates the weight of accuracy (WoA) of each of the segmented image and fed it into the fusion strategy to get the final skin detected region. The last phase involves face localization. The approach is not limited to only frontal face detection but it is invariant with the different head poses, illumination condition, and size of faces. The experimental result demonstrates the improvement in the accuracy and precision but reduction in FPR as compared to other classifiers.