This paper proposes a computer vision method for guiding the robot to greet and guide guests. Locations of guests are acquired for controlling the robot by face detection. In order to reduce regions of search, optical flow algorithm is used to segment image in advance. Asymmetric problems in face detection are explained, and relative solutions are put forward by bootstrapping strategy and asymmetric adaboost algorithm. In addition, fisher discriminant analysis further improves the performance of face detection. And multi-view face models are trained to accommodate practical face detection application. At last, experiments demonstrate that our multi-view face detector achieves high detection accuracy and fast detection speed on both standard testing datasets and real-life images.
['Yutong Gao', 'Xuewei Lv', 'Hongyan Jia']
Real-time multi-view face detection based on optical flow segmentation for guiding the robot