Autonomous video compression system for environmental monitoring
[EN] The monitoring of natural environments is becoming a very controversial topic because people are more and more concerned about preserving and monitoring these natural spaces. The monitoring tasks are usually complemented with a network infrastructure composed by cameras and network devices that...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/148866 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/148866 |
| Access Level: | acceso abierto |
| Palabra clave: | Bandwidth Color spectrum Compression codec Decision algorithm Delay Jitter Packet-loss Quality of experience (QoE) Quality of service (QoS) RGB level RTP Transmission Transcoding Video codec Video monitoring INGENIERIA TELEMATICA |
| Sumario: | [EN] The monitoring of natural environments is becoming a very controversial topic because people are more and more concerned about preserving and monitoring these natural spaces. The monitoring tasks are usually complemented with a network infrastructure composed by cameras and network devices that make easy the remote visualization of the monitored environments. This work presents the design, implementation and test of an autonomous video compression system for environmental monitoring. The system is based on a server in charge of collecting the videos and analyzing the network constraints. As a function of the measured parameters and the predominant color of the requested video, the system determines the best compression codec for transmitting the video through the network. Additionally, the server should run an algorithm developed in Python and MATLAB(c) in charge of analyzing the RED-GREEN-BLUE (RGB) components of the video and performing the transcoding tasks. The system has been tested with different videos and the results of Quality of Service (QoS) and Quality of Experience (QoE) shows that H264 is a good option when the predominant color of videos are black or white while XVID is one the codecs that offer interesting results when colors as red, green or blue are predominant in the video. |
|---|