Indoor 3D Video Monitoring Using Multiple Kinect Depth-Cameras
| Autor: | Mario Martínez-Zarzuela, Francisco Javier Díaz-Pernas, David González-Ortega, M. Pedraza-Hueso, Míriam Antón-Rodríguez |
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| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Computer science business.industry Computer Vision and Pattern Recognition (cs.CV) Controller (computing) Computer Science - Computer Vision and Pattern Recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Point cloud Client USB law.invention Common Object Request Broker Architecture law RGB color model Codec Computer vision Artificial intelligence business Event reconstruction |
| Zdroj: | SSRN Electronic Journal. |
| ISSN: | 1556-5068 |
| Popis: | This article describes the design and development of a system for remote indoor 3D monitoring using an undetermined number of Microsoft(R) Kinect sensors. In the proposed client-server system, the Kinect cameras can be connected to different computers, addressing this way the hardware limitation of one sensor per USB controller. The reason behind this limitation is the high bandwidth needed by the sensor, which becomes also an issue for the distributed system TCP/IP communications. Since traffic volume is too high, 3D data has to be compressed before it can be sent over the network. The solution consists in selfcoding the Kinect data into RGB images and then using a standard multimedia codec to compress color maps. Information from different sources is collected into a central client computer, where point clouds are transformed to reconstruct the scene in 3D. An algorithm is proposed to merge the skeletons detected locally by each Kinect conveniently, so that monitoring of people is robust to self and inter-user occlusions. Final skeletons are labeled and trajectories of every joint can be saved for event reconstruction or further analysis. |
| Databáze: | OpenAIRE |
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