ARC‑SORT is a real‑time, training‑free multi‑object tracker designed for fast, direction‑changing athletes in sports broadcasts. It uses an Interacting Multiple Model Kalman filter to generate per‑track uncertainty‑adaptive search regions (EIoU) and a lightweight corrective identity swap mechanism for track crossings, achieving high HOTA scores on SportsMOT and DanceTrack. The tracker also drops the motion gate for long‑absent players, linking tracklets solely by appearance, and runs at ~50 fps on an RTX 3060 GPU.
By Girish Kumar Adari
arXiv:2609.22706v1 Announce Type: new
Abstract: Identity association in multi-object tracking (MOT) is vulnerable to partial occlusion, truncated detections, and fluctuating confidence scores. Existi...
By Hao Wang
arXiv:2610.10391v1 Announce Type: new
Abstract: End-to-end multi-object trackers have narrowed the gap with classical tracking-by-detection on association-difficult benchmarks. Yet they still make sp...
By Beno\^it Roussel, Damien Bouet, Liming Chen, Pierre Perrault
End-to-end multi-object trackers have narrowed the gap with classical tracking-by-detection on association-difficult benchmarks. Yet they still make spatially implausible errors no classical tracker w...
The paper introduces a deployment‑focused evaluation protocol for pedestrian tracking that isolates tracker performance by using shared detections, assessing initialization, gap continuation, identity recovery, close‑neighbor association, and runtime under load, while still reporting HOTA as an aggregate metric. Applied to the JackRabbot Dataset, the protocol reveals that trackers vary widely in capability, with none maintaining spatially correct, same‑identity output after 1 s of missing detector support, and that runtime on an NVIDIA Jetson Orin often falls below the 10 Hz target in crowded scenes. The authors provide open‑source code and scripts to enable reproducible assessment of tracker suitability for real‑world pedestrian‑centric robotics.
whyItMatters":"The protocol offers a practical, tracker‑only framework that directly informs the design and deployment of mobile robots operating among pedestrians by highlighting specific failure modes and computational constraints that aggregate scores overlook."
By Dominik Wojcikiewicz, Diego Paez-Granados
arXiv:2609.09528v1 Announce Type: new
Abstract: Video large language models (Video-LLMs) are increasingly used as the perceptual front end of world models, a role that assumes they can read motion: h...
By Dhairya Bhatia, Bishoy Galoaa, Oliver Fritsche, Shahid Kamal, Muhammad Obaidullah Abdul Salam, Umer Saleem, Om Rastogi, Frania Felix Chettiar, Nesli Erdogmus, Sarah Ostadabbas