Multi-Object Tracking and Segmentation With Embedding Mask-Based Affinity Fusion in Hierarchical Data Association

In this paper, we propose a highly feasible fully online multi-object tracking and segmentation (MOTS) method that uses instance segmentation results as an input. The proposed method is based on the Gaussian mixture probability hypothesis density (GMPHD) filter, a hierarchical data association (HDA)...

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Veröffentlicht in:	IEEE access 2022, Vol.10, p.60643-60657
Hauptverfasser:	Song, Young-Min, Yoon, Young-Chul, Yoon, Kwangjin, Jang, Hyunsung, Ha, Namkoo, Jeon, Moongu
Format:	Artikel
Sprache:	eng
Schlagworte:	affinity fusion Filtering theory Gaussian mixture probability hypothesis filter Image segmentation instance segmentation Motion segmentation Multi-object tracking online approach Radar tracking Task analysis Three-dimensional displays Tracking tracking by segmentation
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