mlsanityData to 7 Oct 2026

Tracking 6-DoF Object Motion from Events and Frames

arXiv 2103.15568 ↗First posted 29 Mar 2021cs.CVcited by 4

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Abstract (arXiv)

Event cameras are promising devices for lowlatency tracking and high-dynamic range imaging. In this paper,we propose a novel approach for 6 degree-of-freedom (6-DoF)object motion tracking that combines measurements of eventand frame-based cameras. We formulate tracking from highrate events with a probabilistic generative model of the eventmeasurement process of the object. On a second layer, we refinethe object trajectory in slower rate image frames through directimage alignment. We evaluate the accuracy of our approach inseveral object tracking scenarios with synthetic data, and alsoperform experiments with real data.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 7 of its 21 references that are in the map. First posted on arXiv 29 Mar 2021.

Builds on

7 of 21 references.

References · 7

  1. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
  2. 2019Event-based Vision: A Surveycited by 1,010
  3. 2016Direct Sparse Odometrycited by 479
  4. 2018Event-based Moving Object Detection and Trackingcited by 126
  5. 2019EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Camerascited by 46
  6. 2020RGB-D-E: Event Camera Calibration for Fast 6-DOF Object Trackingcited by 12
  7. 2017Independent Motion Detection with Event-driven Camerascited by 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 0; 2026: 1.

4 papers.