Researches And Implement Of Face Detection System For Sign Language Video

Sign language contains not only hand and arm movements, but also other actions such as expression, head and body. The experiment shows that the contents of people understand are not more than 60% if the sign language has only gestures not expressions during the communication. As the premise of expression recognition and head pose estimation, face detection has the important research value. The solutions on the face detection problems are put forward in the sign language video in the paper, which combines the color of skin face detection algorithm with Adaboost face detection algorithm, and finally a face detection system is realized with a high recall rate and a high accuracy rate. Specific researches are as follows:1. Adaboost face detection algorithm is studied in this paper firstly. With the problems of the hand interference in sign language video, lots of hand samples have been put into the negative samples in training classifier, and a positive face classifier has been trained. Owing to the pose varied of head in sign language video, a profile face classifier is trained in this paper. Experimental results show that it has higher accuracy but lower recall rate.2. The color of skin face detection algorithm is studied in this paper. Experimental results show that color of skin face detection algorithm has higher recall rate, but lower precision and accuracy.3. To improve the face detection effect in the sign language video, the color of skin face detection algorithm and Adaboost face detection algorithm are combined. The skin-color segmentation image is scanned by Adaboost face classifier to locate face area accurately. Experimental results show that this method not only has high, and there's a recall rate high precision and accuracy.4. At last, a face detection system, which combines the color of skin face detection algorithm with Adaboost face detection algorithm, has been designed.