ITASK - Intelligent traffic analysis software kit

Minh Triet Tran, Tam V. Nguyen, Trung Hieu Hoang, Trung Nghia Le, Khac Tuan Nguyen, Dat Thanh Dinh, Thanh An Nguyen, Hai Dang Nguyen, Xuan Nhat Hoang, Trong Tung Nguyen, Viet Khoa Vo-Ho, Trong Le Do, Lam Nguyen, Minh Quan Le, Hoang Phuc Nguyen-Dinh, Trong Thang Pham, Xuan Vy Nguyen, E. Ro Nguyen, Quoc Cuong Tran, Hung TranHieu Dao, Mai Khiem Tran, Quang Thuc Nguyen, Tien Phat Nguyen, The Anh Vu-Le, Gia Han Diep, Minh N. Do

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Traffic flow analysis is essential for intelligent transportation systems. In this paper, we introduce our Intelligent Traffic Analysis Software Kit (iTASK) to tackle three challenging problems: vehicle flow counting, vehicle re-identification, and abnormal event detection. For the first problem, we propose to real-time track vehicles moving along the desired direction in corresponding motion-of-interests (MOIs). For the second problem, we consider each vehicle as a document with multiple semantic words (i.e., vehicle attributes) and transform the given problem to classical document retrieval. For the last problem, we propose to forward and backward refine anomaly detection using GAN-based future prediction and backward tracking completely stalled vehicle or sudden-change direction, respectively. Experiments on the datasets of traffic flow analysis from AI City Challenge 2020 show our competitive results, namely, S1 score of 0.8297 for vehicle flow counting in Track 1, mAP score of 0.3882 for vehicle re-identification in Track 2, and S4 score of 0.9059 for anomaly detection in Track 4. All data and source code are publicly available on our project page.

Original languageEnglish (US)
Title of host publicationProceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020
PublisherIEEE Computer Society
Number of pages10
ISBN (Electronic)9781728193601
StatePublished - Jun 2020
Event2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 - Virtual, Online, United States
Duration: Jun 14 2020Jun 19 2020

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516


Conference2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020
Country/TerritoryUnited States
CityVirtual, Online

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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