Real-time traffic sign recognition based on a general purpose GPU and deep-learning
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초록

We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea).

제목
Real-time traffic sign recognition based on a general purpose GPU and deep-learning
저자
Lim, KwangyongHong, YongwonChoi, YeongwooByun, Hyeran
DOI
10.1371/journal.pone.0173317
발행일
2017-03
유형
Article
저널명
PLoS ONE
12
3
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1 ~ 22