mlsanityData to 7 Oct 2026

BodySLAM++: Fast and Tightly-Coupled Visual-Inertial Camera and Human Motion Tracking

arXiv 2309.01236 ↗First posted 3 Sep 2023cs.CV cs.ROcited by 6

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Abstract (arXiv)

Robust, fast, and accurate human state - 6D pose and posture - estimation remains a challenging problem. For real-world applications, the ability to estimate the human state in real-time is highly desirable. In this paper, we present BodySLAM++, a fast, efficient, and accurate human and camera state estimation framework relying on visual-inertial data. BodySLAM++ extends an existing visual-inertial state estimation framework, OKVIS2, to solve the dual task of estimating camera and human states simultaneously. Our system improves the accuracy of both human and camera state estimation with respect to baseline methods by 26% and 12%, respectively, and achieves real-time performance at 15+ frames per second on an Intel i7-model CPU. Experiments were conducted on a custom dataset containing both ground truth human and camera poses collected with an indoor motion tracking system.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 25 of its 35 references that are in the map. First posted on arXiv 3 Sep 2023.

Builds on

25 of 35 references.

References · 25

  1. 2017Mask R-CNNcited by 7,259
  2. 2019Expressive Body Capture: 3D Hands, Face, and Body from a Single Imagecited by 1,600
  3. 2019AMASS: Archive of Motion Capture as Surface Shapescited by 1,208
  4. 2018On the Continuity of Rotation Representations in Neural Networkscited by 1,186
  5. 2016Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,061
  6. 2017End-to-end Recovery of Human Shape and Posecited by 883
  7. 2020ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAMcited by 862
  8. 2016Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Imagecited by 692
  9. 2019Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loopcited by 625
  10. 2019VIBE: Video Inference for Human Body Pose and Shape Estimationcited by 615
  11. 2017VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimatorcited by 418
  12. 2016RMPE: Regional Multi-person Pose Estimationcited by 340
13 more
  1. 2021HuMoR: 3D Human Motion Model for Robust Pose Estimationcited by 319
  2. 2018Learning 3D Human Dynamics from Videocited by 315
  3. 2020HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimationcited by 304
  4. 2020STAR: Sparse Trained Articulated Human Body Regressorcited by 194
  5. 2021GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Camerascited by 151
  6. 2021SPEC: Seeing People in the Wild with an Estimated Cameracited by 134
  7. 2019Fast-SCNN: Fast Semantic Segmentation Networkcited by 124
  8. 2019Exploiting temporal context for 3D human pose estimation in the wildcited by 110
  9. 20203D Human Motion Estimation via Motion Compression and Refinementcited by 98
  10. 2022Pose-NDF: Modeling Human Pose Manifolds with Neural Distance Fieldscited by 85
  11. 2021Adversarial Parametric Pose Priorcited by 38
  12. 2022OKVIS2: Realtime Scalable Visual-Inertial SLAM with Loop Closurecited by 27
  13. 2022BodySLAM: Joint Camera Localisation, Mapping, and Human Motion Trackingcited by 23

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 2; 2026: 2.

6 papers.

  1. 2024TRAM: Global Trajectory and Motion of 3D Humans from in-the-wild Videoscited by 105
  2. 2025PromptHMR: Promptable Human Mesh Recoverycited by 70
  3. 2024Synergistic Global-space Camera and Human Reconstruction from Videoscited by 17
  4. 2025Monocular Person Localization under Camera Ego-motioncited by 1
  5. 2026EgoExoMoCap: Distributed Ego-Exo Human Motion Capturecited by 0
  6. 2026A Review Of Robotic World Models For Dynamic Environments Based On Factor And Scene Graphscited by 0