In this paper, an authenticate live 3D point cloud video streaming system is presented,\nusing a low cost 3D sensor camera, the Microsoft Kinect. The proposed system is implemented on\na client-server network infrastructure. The live 3D video is captured from the Kinect RGB-D sensor,\nthen a 3D point cloud is generated and processed. Filtering and compression are used to handle the\nspatial and temporal redundancies. A color histogram based conditional filter is designed to reduce\nthe color information for each frame based on the mean and standard deviation. In addition to the\ndesigned filter, a statistical outlier removal filter is used. A certificate-based authentication is used\nwhere the client will verify the identity of the server during the handshake process. The processed\n3D point cloud video is live streamed over a TCP/IP protocol to the client. The system is evaluated in\nterms of: compression ratio, total bytes per points, peak signal to noise ratio (PSNR), and Structural\nSimilarity (SSIM) index. The experimental results demonstrate that the proposed video streaming\nsystem have a best case with SSIM 0.859, PSNR of 26.6 dB and with average compression ratio\nof 8.42 while the best average compression ratio case is about 15.43 with PSNR 18.5128 dB of and\nSSIM 0.7936.
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