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Jacobian Computation for Cumulative B-Splines on SE(3) and Application to Continuous-Time Object Tracking

arXiv 2201.10602 ↗First posted 25 Jan 2022cs.CV cs.ROcited by 0

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Abstract (arXiv)

In this paper we propose a method that estimates the SE(3) continuous trajectories (orientation and translation) of the dynamic rigid objects present in a scene, from multiple RGB-D views. Specifically, we fit the object trajectories to cumulative B-Splines curves, which allow us to interpolate, at any intermediate time stamp, not only their poses but also their linear and angular velocities and accelerations. Additionally, we derive in this work the analytical SE(3) Jacobians needed by the optimization, being applicable to any other approach that uses this type of curves. To the best of our knowledge this is the first work that proposes 6-DoF continuous-time object tracking, which we endorse with significant computational cost reduction thanks to our analytical derivations. We evaluate our proposal in synthetic data and in a public benchmark, showing competitive results in localization and significant improvements in velocity estimation in comparison to discrete-time approaches.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 19 of its 54 references that are in the map. First posted on arXiv 25 Jan 2022.

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19 of 54 references.

References · 19

  1. 2017Mask R-CNNcited by 7,259
  2. 2016Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Agecited by 405
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  4. 2018DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenescited by 130
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  7. 2017Continuous-Time Visual-Inertial Odometry for Event Camerascited by 57
  8. 2020DynaSLAM II: Tightly-Coupled Multi-Object Tracking and SLAMcited by 47
  9. 2020VDO-SLAM: A Visual Dynamic Object-aware SLAM Systemcited by 39
  10. 2019Efficient Derivative Computation for Cumulative B-Splines on Lie Groupscited by 28
  11. 2018Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Drivingcited by 26
  12. 2018Efficient Continuous-Time SLAM for 3D Lidar-Based Online Mappingcited by 23
7 more
  1. 2020ClusterVO: Clustering Moving Instances and Estimating Visual Odometry for Self and Surroundingscited by 16
  2. 2020DOT: Dynamic Object Tracking for Visual SLAMcited by 16
  3. 2019The Oxford Multimotion Dataset: Multiple SE(3) Motions with Ground Truthcited by 12
  4. 2021Asynchronous Multi-View SLAMcited by 12
  5. 2018Multimotion Visual Odometry (MVO): Simultaneous Estimation of Camera and Third-Party Motionscited by 8
  6. 2018Trajectory Representation and Landmark Projection for Continuous-Time Structure from Motioncited by 5
  7. 2021Multimotion Visual Odometry (MVO)cited by 4

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