绿眼系统实时识别交通灯颜色与剩余过街时间，助视障者安全通行。
GreenEye: Development of Real-Time Traffic Signal Recognition System for Visual Impairments
- 基于机器学习构建实时交通灯识别系统，可判断颜色与倒计时
- 优化数据分布后，14类识别准确率达99.5%
- 特别适合视障人士日常出行使用
视障人群在过马路时面临识别交通信号灯、判断是否为绿灯以及估算剩余过街时间的重大挑战。以往研究仅关注绿灯与红灯的识别，采用机器学习方法。本文提出绿眼（GreenEye）系统，实现交通信号灯颜色实时识别，并告知行人剩余过街时间。初始训练中最高精度为74.6%，四类识别精度低于40%，主要因数据不平衡导致。通过额外标注和数据库重构，使各类样本数量均衡，优化后所有14类识别精度均达99.5%。
原文摘要 · Abstract (English)
Recognizing a traffic signal, determining if the signal is green or red, and figuring out the time left to cross the crosswalk are significant challenges to visually impaired people. Previous research has focused on recognizing only two traffic signals, green and red lights, using machine learning techniques. The proposed method developed a GreenEye system that recognizes the traffic signals' color and tells the time left for pedestrians to cross the crosswalk in real-time. GreenEye's first training showed the highest precision of 74.6%; four classes reported 40% or lower recognition precision in this training session. The data imbalance caused low precision; thus, extra labeling and database formation were performed to stabilize the number of images between different classes. After the stabilization, all 14 classes showed excelling precision rate of 99.5%.
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