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Olivier Mellina-Gottardo

dblp:24/5266 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none

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

Artificial intelligence and machine learning · 2Graphics, computer vision, multimedia, augmented reality and games · 1

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
Segmentation and scene understanding · 100%
Computer graphics and multimedia
1 paper
Image and video processing · 100%

Topics — the 8 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › Segmentation and scene understanding › image segmentation
active contour model		 0.012004
Gradient Vector Flow Fast Geometric Active Contours · IEEE Trans. Pattern Anal. Mach. Intell. 2004
Computer vision › Segmentation and scene understanding
boundary detection		 0.012004
Gradient Vector Flow Fast Geometric Active Contours · IEEE Trans. Pattern Anal. Mach. Intell. 2004
Computer vision › Segmentation and scene understanding › image segmentation › active contour model
geometric active contours		 0.012004
Gradient Vector Flow Fast Geometric Active Contours · IEEE Trans. Pattern Anal. Mach. Intell. 2004
Computer vision › Segmentation and scene understanding
image segmentation		 0.012004
Gradient Vector Flow Fast Geometric Active Contours · IEEE Trans. Pattern Anal. Mach. Intell. 2004
Image and video processing › image segmentation
active contour		 0.012001
Gradient Vector Flow Fast Geodesic Active Contours · ICCV 2001
Image and video processing › image segmentation › active contour
geodesic active contours		 0.012001
Gradient Vector Flow Fast Geodesic Active Contours · ICCV 2001
Image and video processing
gradient vector flow		 0.012001
Gradient Vector Flow Fast Geodesic Active Contours · ICCV 2001
Image and video processing
image segmentation		 0.012001
Gradient Vector Flow Fast Geodesic Active Contours · ICCV 2001

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

level set formulation · 0.0gradient vector flow · 0.0geodesic active contour flow · 0.0
YearPublicationVenuePosition
2004 Gradient Vector Flow Fast Geometric Active Contours
abstract
In this paper, we propose an edge-driven bidirectional geometric flow for boundary extraction. To this end, we combine the geodesic active contour flow and the gradient vector flow external force for snakes. The resulting motion equation is considered within a level set formulation, can deal with topological changes and important shape deformations. An efficient numerical schema is used for the flow implementation that exhibits robust behavior and has fast convergence rate. Promising results on real and synthetic images demonstrate the potentials of the flow.
Nikos Paragios, Olivier Mellina-Gottardo, Visvanathan Ramesh
 IEEE Trans. Pattern Anal. Mach. Intell.2
2001 Gradient Vector Flow Fast Geodesic Active Contours
Nikos Paragios, Olivier Mellina-Gottardo, Visvanathan Ramesh
 ICCV2