CylindTrack: Depth-Aware Cylindrical Motion Modeling for Panoramic Multi-Object
Overview
CylindTrack is a depth-aware cylindrical tracking-by-detection framework for panoramic multi-object tracking in mobile robots. It addresses coordinate discontinuities and depth estimation fluctuations by jointly modeling panoramic topology and temporal depth consistency. The framework improves identity consistency and trajectory continuity, achieving HOTA scores of 33.67 and 31.12, and IDF1 scores of 40.45 and 34.33 on QuadTrack and JRDB datasets, respectively. It runs at 28.56 and 21.34 frames per second on an NVIDIA GeForce RTX 3090 GPU.
From arXiv Robotics — research abstracts
Event evidence and corrections
0 attributed source owners. Ownership does not establish independent confirmation. Quantities are reported separately and are never added together.
Reported quantity · HOTA score: 33.67 other · Basis not reported · Differing source assertions
“Spherical Geometry-aware Attention to refine depth-aware representations. A Topology-Aware Cylindrical Motion Model (TCMM) represents horizontal motion in an unwrapped angular state and incorporates periodic overlap, angular consistency, and filtered depth cues into association. Experiments on QuadTrack and JRDB demonstrate improved identity consistency and trajectory continuity, with HOTA scores of 33.67 and 31.12 a”
Exact source · revision 2Source owner not reported
Reported quantity · HOTA score: 31.12 other · Basis not reported · Differing source assertions
“Spherical Geometry-aware Attention to refine depth-aware representations. A Topology-Aware Cylindrical Motion Model (TCMM) represents horizontal motion in an unwrapped angular state and incorporates periodic overlap, angular consistency, and filtered depth cues into association. Experiments on QuadTrack and JRDB demonstrate improved identity consistency and trajectory continuity, with HOTA scores of 33.67 and 31.12 a”
Exact source · revision 2Source owner not reported
Artifact availability · code: reported pending
“nd IDF1 scores of 40.45 and 34.33, respectively. The framework processes 28.56 and 21.34 frames per second, respectively, on an NVIDIA GeForce RTX 3090 GPU under the reported evaluation settings. These results support persistent panoramic multi-object tracking for mobile robot perception. The source code will be released at https://github.com/warriordby/CylindTrack.”
Exact source · revision 2Source owner not reported
Evidence dependency changes (1)
- 2026-10-31T05:20:20.413Z · evidence updated · source revision 2. Evidence extraction was updated; current source attributions are shown above.
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- arXiv Robotics — research abstractsSignalCylindTrack: Depth-Aware Cylindrical Motion Modeling for Panoramic Multi-Object Tracking in Mobile Robots
CylindTrack is a depth-aware cylindrical tracking-by-detection framework for panoramic multi-object tracking in mobile robots. It addresses coordinate discontinuities and depth estimation fluctuations by jointly modeling panoramic topology and temporal depth consistency. The framework improves identity consistency and trajectory continuity, achieving HOTA scores of 33.67 and 31.12, and IDF1 scores of 40.45 and 34.33 on QuadTrack and JRDB datasets, respectively. It runs at 28.56 and 21.34 frames per second on an NVIDIA GeForce RTX 3090 GPU.
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