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Francois Ayoub

dblp:385/1457 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%
Artificial intelligence
1 paper
3D vision · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics
visual analytics
0.812024
Opening the Black Box of 3D Reconstruction Error Analysis with VECTOR · IEEE VIS 2024
Visualization and visual analytics › visual analytics
visual analytics system
0.812024
Opening the Black Box of 3D Reconstruction Error Analysis with VECTOR · IEEE VIS 2024
Computer vision › 3D vision › 3d reconstruction › multi-view stereo
stereo reconstruction
0.212024
Opening the Black Box of 3D Reconstruction Error Analysis with VECTOR · IEEE VIS 2024

Methods — techniques the papers use, named apart from their topics

visual analysis · 1.5bundle adjustment · 1.5
YearPublicationVenuePosition
2024 Opening the Black Box of 3D Reconstruction Error Analysis with VECTOR
abstract
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.
Racquel Fygenson, Kazi Jawad, Isabel Li, Francois Ayoub, Robert G. Deen, Scott Davidoff, Dominik Moritz, Mauricio Hess-Flores
IEEE VIS4