Human Face Detection Algorithm Research Articles

Development of a fast transmission method for 3D point cloud

In this paper, a transmission method of the 3D point cloud data of the object upper body is proposed. The key idea of the method is to reduce the amount of transmission data in the condition of retaining the necessary information. In our system, the unnecessary information is removed by using filters and the segmentation algorithm. Three P frames (Predicted frame) are inserted between two I frames (Intra frame) to further improve the transmission rate. The I frame of large size includes all the vision information that is related to the object upper body, while the P frame includes only the information of the small change in the current frame, whose size is smaller than the former. In order to acquire the information of the P frame, first, a human face detection algorithm based on the machine learning technology is implemented. Then, a coarse-to-fine approach is used to detect the nose tip which helps to improve the precision of acquiring the human faces information. The experiment result demonstrates that the proposed method is able to reduce the time delay of processing and transmission and to lower the compression ratio with an allowable distortion rate.

Application of computer image processing in office automation system

With the development of science and technology, a variety of office automation systems (OAS) has been extensively applied in various occasions. Moreover, digital image processing technology has made great progress. The emergence of a series of excellent algorithms represented by Adaboost human face detection algorithm extends the application space of digital image processing in daily work and study. Besides, the operational capability of existing personal computers enables them to run smoothly these algorithms, which further contributes to the technological maturity of the digital image processing associated office automation systems. To keep up with the pace of information technology, this study selects high definition (HD) technology for paper archives in OAS, which is related to digital image processing as the research content. Automatic high definition demonstration of paper archives can reduce the burden on staff. This paper solved the problems of correction of slanted document image, automatic extraction of identification photo and color enhancement of seal and verified the feasibility of the scheme.

An efficient algorithm for human face detection and facial feature extraction under different conditions

In this paper, an efficient algorithm for human face detection and facial feature extraction is devised. Firstly, the location of the face regions is detected using the genetic algorithm and the eigenface technique. The genetic algorithm is applied to search for possible face regions in an image, while the eigenface technique is used to determine the fitness of the regions. As the genetic algorithm is computationally intensive, the searching space is reduced and limited to the eye regions so that the required timing is greatly reduced. Possible face candidates are then further verified by measuring their symmetries and determining the existence of the different facial features. Furthermore, in order to improve the level of detection reliability in our approach, the lighting effect and orientation of the faces are considered and solved.