2020
DOI: 10.31219/osf.io/brhu5
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Quick Overview for Multi-target Tracking

Abstract: Tracking an unknown and time-varying number of targets (e.g., speakers) in indoor environments using audio-visual (AV) modalities has received increasing interest in numerous fields including video conferencing, individual speaker discrimination, and human-computer interaction. The audio-visual sequential Monte Carlo probability hypothesis density (AV-SMC-PHD) filter is a popular baseline for multi-target tracking, offering an elegant framework for fusing audio-visual information and dealing with a varying num… Show more

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