Marvin Anas Hahn

dblp:207/0797 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · unresolved

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

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 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.

Artificial intelligence
1 paper
3D vision · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision › camera calibration
camera model
0.912025
Order-One Rolling Shutter Cameras · CVPR 2025
Computer vision › 3D vision
camera pose estimation
0.912025
Order-One Rolling Shutter Cameras · CVPR 2025
Computer vision › 3D vision › camera pose estimation
relative pose estimation
0.912025
Order-One Rolling Shutter Cameras · CVPR 2025
Computer vision › 3D vision › camera calibration › camera model
rolling shutter camera
0.912025
Order-One Rolling Shutter Cameras · CVPR 2025

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

minimal problem classification · 0.9algebraic geometry · 0.9
YearPublicationVenuePosition
2025 Order-One Rolling Shutter Cameras
abstract
Rolling shutter (RS) cameras dominate consumer and smartphone markets. Several methods for computing the absolute pose of RS cameras have appeared in the last 20 years, but the relative pose problem has not been fully solved yet. We provide a unified theory for the important class of order-one rolling shutter (RS1) cameras. These cameras generalize the perspective projection to RS cameras, projecting a generic space point to exactly one image point via a rational map. We introduce a new back-projection RS camera model, characterize RS1cameras, construct explicit parameterizations of such cameras, and determine the image of a space line. We classify all minimal problems for solving the relative camera pose problem with linear RS1cameras and discover new practical cases. Finally, we show how the theory can be used to explain RS models previously used for absolute pose computation.
Marvin Anas Hahn, Kathlén Kohn, Orlando Marigliano, Tomás Pajdla
CVPR1