Optimisation of pedestrian detection system using FPGA-CPU hybrid implementation for vehicle industry
Küçük Resim Yok
Tarih
2019
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Inderscience Enterprises Ltd.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Improved image processing and developing technologies are rapidly expanding the application areas of image processing systems. In recent years, pedestrian detection systems have become one of the major safety technologies used in the automotive industry. This paper presents an optimised real-time pedestrian detection system using an FPGA-CPU based hybrid design. The histograms of oriented gradients (HOG) algorithm, which is extensively used for feature extraction in pedestrian detection applications, was implemented on a low-end FPGA. In the study, the original HOG descriptors are designed in low complexity without sacrificing performance. The obtained features were classified on a low-power single board computer with support vector machine (SVM). Tests with the INRIA pedestrian database show that the proposed model has high potential for use as a real-time low-cost pedestrian detection system in practice.
Açıklama
Anahtar Kelimeler
Optimisation, Vehicle design, HOG, Histogram of oriented gradients, Computer vision, Pedestrian detection, FPGA, Field programmable gate arrays (FPGA), Hybrid vehicles, Image enhancement, Pedestrian safety, Real time systems, Support vector machines, Application area, Histograms of oriented gradients (HoG), Hybrid implementation, Image processing system, Pedestrian detection, Pedestrian detection system, Safety technology, Single board computers, Feature extraction
Kaynak
International Journal of Vehicle Design
WoS Q Değeri
Q4
Scopus Q Değeri
Q4
Cilt
80
Sayı
2-4
SI
SI
Künye
Özcan, A. R. & Tavşanoğlu, A. V. (2019). Optimisation of pedestrian detection system using FPGA-CPU hybrid implementation for vehicle industry. International Journal of Vehicle Design, 80(2-4) doi:10.1504/IJVD.2019.109865
