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Sergio Garrido-Jurado

dblp:188/9671 · DBLP profile ↗
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6ranked-venue papers
3as first author
0since 2021 · last 2018
0000-0001-6872-7458ORCID · verified

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

Artificial intelligence and machine learning · 3 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 3 · 1 first-author

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
Virtual and augmented reality · 75% Visual content generation and editing · 25%

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

TopicWeightPapersLastEvidence papers
Virtual and augmented reality › immersive interaction
collaborative virtual environments
0.312018
Oasis: Procedurally Generated Social Virtual Spaces from 3D Scanned Real Spaces · IEEE Trans. Vis. Comput. Graph. 2018
Visual content generation and editing
procedural content generation
0.312018
Oasis: Procedurally Generated Social Virtual Spaces from 3D Scanned Real Spaces · IEEE Trans. Vis. Comput. Graph. 2018
Virtual and augmented reality › virtual environment
virtual environment generation
0.312018
Oasis: Procedurally Generated Social Virtual Spaces from 3D Scanned Real Spaces · IEEE Trans. Vis. Comput. Graph. 2018
Virtual and augmented reality
virtual reality
0.312018
Oasis: Procedurally Generated Social Virtual Spaces from 3D Scanned Real Spaces · IEEE Trans. Vis. Comput. Graph. 2018

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

real walking · 0.3depth sensing · 0.33d scanning · 0.3
YearPublicationVenuePosition
2018 Robust identification of fiducial markers in challenging conditions
Víctor Manuel Mondéjar-Guerra, Sergio Garrido-Jurado, Rafael Muñoz-Salinas, Manuel J. Marín-Jiménez, Rafael Medina Carnicer
Expert Syst. Appl.2
2018 Oasis: Procedurally Generated Social Virtual Spaces from 3D Scanned Real Spaces
abstract
We present Oasis, a novel system for automatically generating immersive and interactive virtual reality environments for single and multiuser experiences. Oasis enables real-walking in the generated virtual environment by capturing indoor scenes in 3D and mapping walkable areas. It makes use of available depth information for recognizing objects in the real environment which are paired with virtual counterparts to leverage the physicality of the real world, for a more immersive virtual experience. Oasis allows co-located and remotely located users to interact seamlessly and walk naturally in a shared virtual environment. Experiencing virtual reality with currently available devices can be cumbersome due to presence of objects and furniture which need to be removed every time the user wishes to use VR. Our approach is new, in that it allows casual users to easily create virtual reality environments in any indoor space without rearranging furniture or requiring specialized equipment, skill or training. We demonstrate our approach to overlay a virtual environment over an existing physical space through fully working single and multiuser systems implemented on a Tango tablet device.
Misha Sra, Sergio Garrido-Jurado, Pattie Maes
IEEE Trans. Vis. Comput. Graph.2
2016 Procedurally generated virtual reality from 3D reconstructed physical space
abstract
We present a novel system for automatically generating immersive and interactive virtual reality (VR) environments using the real world as a template. The system captures indoor scenes in 3D, detects obstacles like furniture and walls, and maps walkable areas (WA) to enable real-walking in the generated virtual environment (VE). Depth data is additionally used for recognizing and tracking objects during the VR experience. The detected objects are paired with virtual counterparts to leverage the physicality of the real world for a tactile experience. Our approach is new, in that it allows a casual user to easily create virtual reality worlds in any indoor space of arbitrary size and shape without requiring specialized equipment or training. We demonstrate our approach through a fully working system implemented on the Google Project Tango tablet device.
Misha Sra, Sergio Garrido-Jurado, Chris Schmandt
VRST2
2016 Simultaneous reconstruction and calibration for multi-view structured light scanning
Sergio Garrido-Jurado, Rafael Muñoz-Salinas, Francisco José Madrid-Cuevas, Manuel J. Marín-Jiménez
J. Vis. Commun. Image Represent.1
2016 Generation of fiducial marker dictionaries using Mixed Integer Linear Programming
Sergio Garrido-Jurado, Rafael Muñoz-Salinas, Francisco José Madrid-Cuevas, Rafael Medina Carnicer
Pattern Recognit.1
2014 Automatic generation and detection of highly reliable fiducial markers under occlusion
Sergio Garrido-Jurado, Rafael Muñoz-Salinas, Francisco José Madrid-Cuevas, Manuel J. Marín-Jiménez
Pattern Recognit.1