標題: CORRELATION-BASED FACE DETECTION FOR RECOGNIZING FACES IN VIDEOS
作者: Hsu, Heng-Wei
Wu, Tung-Yu
Wong, Wing Hung
Lee, Chen-Yi
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
關鍵字: Convolutional neural network;deep learning;neuron selection;face detection;face recognition
公開日期: 1-Jan-2018
摘要: Finding the locations and identities of faces in videos is a very important task in numerous applications. In this paper, we propose a correlation-based face detection approach to improve the performance of face recognition tasks for videos. We apply correlation measures to pairs of response maps which are generated from automatically selected neurons in deep convolutional neural network (CNN) models to detect faces in each video frame. The embeddings extracted from faces cropped by our proposed approach are more consistent across each video sequence and more suitable for face recognition and clustering tasks. Experimental results from the YouTube Faces (YTF) dataset demonstrate that our proposed approach is more robust and achieves better recognition accuracy compared to state-of-the-art face detection approaches.
URI: http://hdl.handle.net/11536/150764
期刊: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
起始頁: 3101
結束頁: 3105
Appears in Collections:Conferences Paper