mlsanityData to 7 Oct 2026

Opening the Black Box of 3D Reconstruction Error Analysis with VECTOR

arXiv 2408.03503 ↗First posted 7 Aug 2024cs.CV cs.ROcited by 0

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Abstract (arXiv)

Reconstruction of 3D scenes from 2D images is a technical challenge that impacts domains from Earth and planetary sciences and space exploration to augmented and virtual reality. Typically, reconstruction algorithms first identify common features across images and then minimize reconstruction errors after estimating the shape of the terrain. This bundle adjustment (BA) step optimizes around a single, simplifying scalar value that obfuscates many possible causes of reconstruction errors (e.g., initial estimate of the position and orientation of the camera, lighting conditions, ease of feature detection in the terrain). Reconstruction errors can lead to inaccurate scientific inferences or endanger a spacecraft exploring a remote environment. To address this challenge, we present VECTOR, a visual analysis tool that improves error inspection for stereo reconstruction BA. VECTOR provides analysts with previously unavailable visibility into feature locations, camera pose, and computed 3D points. VECTOR was developed in partnership with the Perseverance Mars Rover and Ingenuity Mars Helicopter terrain reconstruction team at the NASA Jet Propulsion Laboratory. We report on how this tool was used to debug and improve terrain reconstruction for the Mars 2020 mission.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 34 references that are in the map. First posted on arXiv 7 Aug 2024.

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References · 7

  1. 2015ORB-SLAM: a Versatile and Accurate Monocular SLAM Systemcited by 983
  2. 2019The What-If Tool: Interactive Probing of Machine Learning Modelscited by 207
  3. 2018Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontierscited by 117
  4. 2019FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learningcited by 93
  5. 2018RuleMatrix: Visualizing and Understanding Classifiers with Rulescited by 62
  6. 2020A Visual Analytics Approach to Debugging Cooperative, Autonomous Multi-Robot Systems' Worldviewscited by 3
  7. 2023Lessons from the Development of an Anomaly Detection Interface on the Mars Perseverance Rover using the ISHMAP Frameworkcited by 1

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