GRACE: Geometry- and Ray-Aware Camera-Efficient Multi-View Pedestrian Tracking

Taigo Sakai, Kazuhiro Hotta, Hiroki Kouno, Naoki Kato
9/15/2026
cs.CV

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Abstract

Reducing the number of cameras reduces the deployment cost but removes views that correct BEV responses stretched away from true pedestrian positions by projection and short score drops that can split tracks} in Bird's-Eye View (BEV) tracking. We introduce GRACE, a camera-efficient multi-view tracker with three components. Volumetric-Guided Fusion combines homography-based BEV features with features lifted through 3D space. Ray Conditioning exposes each camera's viewing direction to the fusion network. Its tracking component, BEV Track Recovery (BTR), uses low-confidence detections only to continue existing tracks. The same detections cannot start new tracks. With two WildTrack cameras, GRACE improves MOTA from 83.54 for TrackTacular, our baseline, to 91.07.

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Cite this paper

@article{sakai2026grace,
  title  = {GRACE: Geometry- and Ray-Aware Camera-Efficient Multi-View Pedestrian Tracking},
  author = {Taigo Sakai and Kazuhiro Hotta and Hiroki Kouno and Naoki Kato},
  year   = {2026},
  eprint = {2609.16872},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2609.16872v1}
}

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