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GenTrack2 proposes a multi-object tracking method combining stochastic and deterministic approaches

GenTrack2 proposes a visual multi-object tracking method that jointly uses stochastic particle filtering and deterministic association to maintain identifier consistency under conditions where the number of targets is unknown and changes over time and the dynamics are nonlinear. The particle filter uses particle swarm optimization (PSO) to guide particles toward the modes of the state distribution, with a fitness measure that combines motion consistency, appearance similarity, and social-interaction cues with neighboring targets; deterministic association strengthens identifier consistency through a cost matrix that incorporates spatial consistency between particles and current detections, detection confidence, and track penalties.

Part of the event: GenTrack2 Multi-Object Tracking Method Paper Released

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