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.