CylindTrack: Depth-Aware Cylindrical Motion Modeling for Panoramic Multi-Object Tracking in Mobile Robots
CylindTrack: 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.
CylindTrack introduces a depth-aware cylindrical tracking framework for panoramic multi-object tracking in mobile robots, addressing challenges in coordinate continuity and depth estimation. The method improves identity consistency and trajectory continuity with reported HOTA and IDF1 scores, and achieves real-time performance on standard hardware.
Source: arXiv Robotics — research abstracts · Read original article ↗
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What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
Reported numbers
HOTA score
33.67
View original evidence
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
Open source S4HOTA score
31.12
View original evidence
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
Open source S4
- code: not_reported
- code: Reported pending Open source S5
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
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
Open source S4
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.
Open source S5
Source：arXiv Robotics — research abstracts · arxiv.org