mlsanityData to 7 Oct 2026

TrackMe:A Simple and Effective Multiple Object Tracking Annotation Tool

arXiv 2410.15518 ↗First posted 20 Oct 2024cs.CVcited by 0

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Abstract (arXiv)

Object tracking, especially animal tracking, is one of the key topics that attract a lot of attention due to its benefits of animal behavior understanding and monitoring. Recent state-of-the-art tracking methods are founded on deep learning architectures for object detection, appearance feature extraction and track association. Despite the good tracking performance, these methods are trained and evaluated on common objects such as human and cars. To perform on the animal, there is a need to create large datasets of different types in multiple conditions. The dataset construction comprises of data collection and data annotation. In this work, we put more focus on the latter task. Particularly, we renovate the well-known tool, LabelMe, so as to assist common user with or without in-depth knowledge about computer science to annotate the data with less effort. The new tool named as TrackMe inherits the simplicity, high compatibility with varied systems, minimal hardware requirement and convenient feature utilization from the predecessor. TrackMe is an upgraded version with essential features for multiple object tracking annotation.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 11 of its 21 references that are in the map. First posted on arXiv 20 Oct 2024.

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11 of 21 references.

References · 11

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2016Simple Online and Realtime Trackingcited by 862
  3. 2021ByteTrack: Multi-Object Tracking by Associating Every Detection Boxcited by 812
  4. 2018GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wildcited by 471
  5. 2021MOTR: End-to-End Multiple-Object Tracking with Transformercited by 379
  6. 2022Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Trackingcited by 345
  7. 2020GMOT-40: A Benchmark for Generic Multiple Object Trackingcited by 32
  8. 2022Multi-Camera Multiple 3D Object Tracking on the Move for Autonomous Vehiclescited by 19
  9. 2022Multi-Camera Multi-Object Tracking on the Move via Single-Stage Global Association Approachcited by 7
  10. 2023Z-GMOT: Zero-shot Generic Multiple Object Trackingcited by 7
  11. 2024TP-GMOT: Tracking Generic Multiple Object by Textual Prompt with Motion-Appearance Cost (MAC) SORTcited by 2

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