SimpleTrack: Rethinking and Improving the JDE Approach for Multi-Object Tracking Article Swipe
Jiaxin Li
,
Yan Ding
,
Hua‐Liang Wei
,
Yutong Zhang
,
Wenxiang Lin
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/s22155863
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/s22155863
Joint detection and embedding (JDE) methods usually fuse the target motion information and appearance information as the data association matrix, which could fail when the target is briefly lost or blocked in multi-object tracking (MOT). In this paper, we aim to solve this problem by proposing a novel association matrix, the Embedding and GioU (EG) matrix, which combines the embedding cosine distance and GioU distance of objects. To improve the performance of data association, we develop a simple, effective, bottom-up fusion tracker for re-identity features, named SimpleTrack, and propose a new tracking strategy which can mitigate the loss of detection targets. To show the effectiveness of the proposed method, experiments are carried out using five different state-of-the-art JDE-based methods. The results show that by simply replacing the original association matrix with our EG matrix, we can achieve significant improvements in IDF1, HOTA and IDsw metrics, and increase the tracking speed of these methods by around 20%. In addition, our SimpleTrack has the best data association capability among the JDE-based methods, e.g., 61.6 HOTA and 76.3 IDF1, on the test set of MOT17 with 23 FPS running speed on a single GTX2080Ti GPU.
Related Topics
Concepts
Embedding
Fuse (electrical)
Computer science
Tracking (education)
Cosine similarity
Association (psychology)
Matrix (chemical analysis)
Data association
Distance matrix
Computer vision
Artificial intelligence
Video tracking
Object (grammar)
Set (abstract data type)
Data mining
Pattern recognition (psychology)
Algorithm
Engineering
Epistemology
Philosophy
Electrical engineering
Psychology
Materials science
Programming language
Filter (signal processing)
Pedagogy
Composite material
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s22155863
- https://www.mdpi.com/1424-8220/22/15/5863/pdf?version=1659699500
- OA Status
- gold
- Cited By
- 53
- References
- 50
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4221162155
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4221162155Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s22155863Digital Object Identifier
- Title
-
SimpleTrack: Rethinking and Improving the JDE Approach for Multi-Object TrackingWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-08-05Full publication date if available
- Authors
-
Jiaxin Li, Yan Ding, Hua‐Liang Wei, Yutong Zhang, Wenxiang LinList of authors in order
- Landing page
-
https://doi.org/10.3390/s22155863Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/22/15/5863/pdf?version=1659699500Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1424-8220/22/15/5863/pdf?version=1659699500Direct OA link when available
- Concepts
-
Embedding, Fuse (electrical), Computer science, Tracking (education), Cosine similarity, Association (psychology), Matrix (chemical analysis), Data association, Distance matrix, Computer vision, Artificial intelligence, Video tracking, Object (grammar), Set (abstract data type), Data mining, Pattern recognition (psychology), Algorithm, Engineering, Epistemology, Philosophy, Electrical engineering, Psychology, Materials science, Programming language, Filter (signal processing), Pedagogy, Composite materialTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
53Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 10, 2024: 26, 2023: 13, 2022: 4Per-year citation counts (last 5 years)
- References (count)
-
50Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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