AIC2018 Report: Traffic Surveillance Research

Tingyu Mao,Wei Zhang,Haoyu He,Yanjun Lin,Vinay Kale,Alexander Stein,Zoran Kostic

PROCEEDINGS 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW)（2018）

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摘要

Traffic surveillance and management technologies are some of the most intriguing aspects of smart city applications. In this paper, we investigate and present the methods for vehicle detections, tracking, speed estimation and anomaly detection for NVIDIA AI City Challenge 2018 (AIC2018). We applied Mask-RCNN and deep-sort for vehicle detection and tracking in track 1, and optical flow based method in track 2. In track 1, we achieve 100% detection rate and 7.97 mile/hour estimation error for speed estimation.

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关键词

Mask-RCNN,vehicle detection,speed estimation,AIC2018 report,management technologies,anomaly detection,NVIDIA AI City Challenge 2018,smart city,traffic surveillance

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