| Autor: |
Abdelouahed Abounada, Assia Arsalane, Smail Bariko, Abdessamad Klilou |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
2020 International Symposium on Advanced Electrical and Communication Technologies (ISAECT). |
| DOI: |
10.1109/isaect50560.2020.9523671 |
| Popis: |
Detecting moving objects based on real-time video processing is considered as a challenging task. The background subtraction using the Gaussian Mixture Model (GMM) is one of the widely used technique. However, it requires high-computing power to meet real-time processing constraints. An efficient implementation of GMM algorithm on an embedded platform based on the C6678 digital signal processor (DSP) was proposed in this paper. First, an optimized GMM code has been developed for the proposed embedded platform. Then, an efficient memory management strategy has been implemented to ensure contiguous memory access. In addition, the compiler options have been enabled to take profit from loops unrolling and software pipelining to improve the computing performances. In order to evaluate the quality of our implementation, a metrics comparison have been performed based on the background truth images provided by the literature dataset references. Experimental results show important improvements over the optimized implementation of the state-of-the-art. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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