Variational, Geometric, and Level Set Methods in Computer Vision | Zendy

Gabriel Peyré | Zendy; Laurent D. Cohen | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Variational, Geometric, and Level Set Methods in Computer Vision

Author(s) -

Gabriel Peyré,

Laurent D. Cohen

Publication year - 2005

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

DOI - 10.1007/11567646

Subject(s) - computer vision , computer science , artificial intelligence , segmentation , path (computing) , motion (physics) , set (abstract data type) , stereopsis , structure from motion , computer graphics (images) , programming language

International audienceIn this paper we present a simple modification of the Fast Marching algorithm to speed up the computation using a heuristic. This modification leads to an algorithm that is similar in spirit to the A* algorithm used in artificial intelligence. Using a heuristic allows to extract geodesics from a single source to a single goal very quickly and with a low memory requirement. Any application that needs to compute a lot of geodesic paths can gain benefits from our algorithm. The computational saving is even more important for 3D medical images with tubular structures and for higher dimensional data

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research