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New ARC-SORT tracker improves sports broadcast multi-object tracking

Researchers have developed ARC-SORT, a new multi-object tracking system designed for sports broadcasts that operates in real-time without requiring any training. The system measures its own uncertainty to adapt its tracking behavior, using an Interacting Multiple Model (IMM) Kalman filter to define search regions based on prediction reliability. ARC-SORT achieved high accuracy on the SportsMOT and DanceTrack datasets, outperforming existing methods in terms of tracking accuracy and identity switches, and runs efficiently on consumer hardware. AI

IMPACT This new tracking algorithm could improve automated analysis and fan engagement in sports broadcasts.

RANK_REASON This is a research paper detailing a new algorithm and its performance on benchmarks. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New ARC-SORT tracker improves sports broadcast multi-object tracking

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This is a research paper detailing a new algorithm and its performance on benchmarks. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Girish Kumar Adari ·

    ARC-SORT: Adaptive, Robust, Compensated Multi-Object Tracking with Interacting Multiple Models

    arXiv:2610.22306v1 Announce Type: new Abstract: Multi-object tracking in sports broadcasts is hard for two reasons: athletes move fast and change direction abruptly, and the camera pans and zooms at the same time. We present ARC-SORT (Adaptive, Robust, Compensated SORT), a tracki…