학술논문
Multi-Class Multi-Movement Vehicle Counting Based on CenterTrack
Document Type
Conference
Author
Source
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) CVPRW Computer Vision and Pattern Recognition Workshops (CVPRW), 2021 IEEE/CVF Conference on. :4004-4010 Jun, 2021
Subject
Language
ISSN
2160-7516
Abstract
In this paper we present our approach to the Track 1 of the 2021 AI City Challenge. The goal of the challenge track is to to analyse footage captured with traffic cameras by counting the number of vehicles performing various predefined motions of interest. Our approach is based on the CenterTrack object detection and tracking neural network used in conjunction with a simple IoU-based tracking algorithm. In the public evaluation server our system achieved the S1 score of 0.8449 placing it at the 8th place on the public leaderboard.