Online Action Detection in Surveillance Scenarios: A Comprehensive Review and Comparative Study of State-of-the-Art Multi-Object Tracking Methods-Reference-Cited by-同舟云学术

Online Action Detection in Surveillance Scenarios: A Comprehensive Review and Comparative Study of State-of-the-Art Multi-Object Tracking Methods

Author:

Alikhanov Jumabek¹,Kim Hakil¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, Inha University, Incheon, South Korea

Funder

Brain Korea (BK) 21 Four Program funded by the Ministry of Education (MOE) and National Research Foundation (NSF) of Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference31 articles.

1. MOT20: A benchmark for multi object tracking in crowded scenes;dendorfer;arXiv 2003 09003,2020

3. MOT16: A benchmark for multi-object tracking;milan;arXiv 1603 00831 [cs],2016

4. DanceTrack: An evaluation set for the study of human motion tracking;sarafianos;Proc Eur Conf Comput Vis (ECCV),2020

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1. FocoTrack: Multi Object Tracking by Focusing On Overlap at Low Frame Rate;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

4. An Interactive Annotation Method Based on Incremental Learning;2023 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML);2023-11-03