Design of a Low-Power Embedded System Based on a SoC-FPGA and the Honeybee Search Algorithm for Real-Time Video Tracking

Autor: Cesar Puente, Gustavo Olague, Oscar Ernesto Pérez Cham, Emilio J. Gonzalez-Galvan, Luis Javier Ontañón García Pimentel, Juan C. Cuevas-Tello, Carlos Soubervielle-Montalvo, Carlos Arturo Aguirre-Salado
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Sensors; Volume 22; Issue 3; Pages: 1280
Sensors, Vol 22, Iss 1280, p 1280 (2022)
ISSN: 1424-8220
DOI: 10.3390/s22031280
Popis: Video tracking involves detecting previously designated objects of interest within a sequence of image frames. It can be applied in robotics, unmanned vehicles, and automation, among other fields of interest. Video tracking is still regarded as an open problem due to a number of obstacles that still need to be overcome, including the need for high precision and real-time results, as well as portability and low-power demands. This work presents the design, implementation and assessment of a low-power embedded system based on an SoC-FPGA platform and the honeybee search algorithm (HSA) for real-time video tracking. HSA is a meta-heuristic that combines evolutionary computing and swarm intelligence techniques. Our findings demonstrated that the combination of SoC-FPGA and HSA reduced the consumption of computational resources, allowing real-time multiprocessing without a reduction in precision, and with the advantage of lower power consumption, which enabled portability. A starker difference was observed when measuring the power consumption. The proposed SoC-FPGA system consumed about 5 Watts, whereas the CPU-GPU system required more than 200 Watts. A general recommendation obtained from this research is to use SoC-FPGA over CPU-GPU to work with meta-heuristics in computer vision applications when an embedded solution is required.
Databáze: OpenAIRE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje