Color Reduction in an Authenticate Live 3D Point Cloud Video Streaming System
| Autor: | Sandro Wefel, Zainab Namh Sultani, Rana F. Al-Tuma |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Color histogram
video streaming Computer Networks and Communications Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Point cloud 02 engineering and technology lcsh:QA75.5-76.95 0202 electrical engineering electronic engineering information engineering Computer vision live 3D point cloud Authentication business.industry 020206 networking & telecommunications Filter (signal processing) filtering compression Peak signal-to-noise ratio Video compression picture types Human-Computer Interaction Embedded system Compression ratio Microsoft Kinect authentication x509 certificate RGB color model 020201 artificial intelligence & image processing lcsh:Electronic computers. Computer science Artificial intelligence business |
| Zdroj: | Computers; Volume 5; Issue 3; Pages: 17 Computers, Vol 5, Iss 3, p 17 (2016) |
| ISSN: | 2073-431X |
| DOI: | 10.3390/computers5030017 |
| Popis: | In this paper, an authenticate live 3D point cloud video streaming system is presented, using a low cost 3D sensor camera, the Microsoft Kinect. The proposed system is implemented on a client-server network infrastructure. The live 3D video is captured from the Kinect RGB-D sensor, then a 3D point cloud is generated and processed. Filtering and compression are used to handle the spatial and temporal redundancies. A color histogram based conditional filter is designed to reduce the color information for each frame based on the mean and standard deviation. In addition to the designed filter, a statistical outlier removal filter is used. A certificate-based authentication is used where the client will verify the identity of the server during the handshake process. The processed 3D point cloud video is live streamed over a TCP/IP protocol to the client. The system is evaluated in terms of: compression ratio, total bytes per points, peak signal to noise ratio (PSNR), and Structural Similarity (SSIM) index. The experimental results demonstrate that the proposed video streaming system have a best case with SSIM 0.859, PSNR of 26.6 dB and with average compression ratio of 8.42 while the best average compression ratio case is about 15.43 with PSNR 18.5128 dB of and SSIM 0.7936. |
| Databáze: | OpenAIRE |
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