使用深度学习的脆弱行人检测和跟踪

Hyok Song, Inkyu Choi, M. Ko, J. Bae, Sooyoung Kwak, Jisang Yoo
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引用次数: 19

摘要

人行横道周围易受伤害的行人发生的事故不断,因此需要主动的安全支持系统。我们的研究包括弱势行人行为特征演绎、行人行为分析模块开发以及利用大数据分析进行主动安全保障系统的安全系统开发。本文展示了使用深度学习的行人/汽车检测、跟踪和动作识别系统,该系统使用来自首尔国立大学安装的闭路电视的视频流。该算法采用SSD(Single shot multibox detector,单镜头多盒检测器)结构和移动网络,处理速度更快,检测率更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vulnerable pedestrian detection and tracking using deep learning
Accidents related with vulnerable pedestrians around crosswalks are continued so that proactive safety support system is required. Our research includes vulnerable pedestrian action character deduction, pedestrian action analysis module development and safety system development using big data analysis for the proactive safety support system. This paper shows pedestrian/car detection, tracking and action recognition system using deep learning using video streams which come from CCTVs installed at SNU(Seoul National University). This algorithm includes SSD(Single shot multibox detector) structure and mobilenets for faster process and higher detection ratio.
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