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Conference papers
3D Object detection and viewpoint selection in sketch images using local patch-based Zernike moments
Abstract : In this paper we present a new approach to detect and
recognize 3D models in 2D storyboards which have been
drawn during the production process of animated cartoons.
Our method is robust to occlusion, scale and rotation. The
lack of texture and color makes it difficult to extract local
features of the target object from the sketched storyboard.
Therefore the existing approaches using local descriptors
like interest points can fail in such images. We propose
a new framework which combines patch-based Zernike descriptors
with a method enforcing spatial constraints for exactly
detecting 3D models represented as a set of 2D views
in the storyboards. Experimental results show that the proposed
method can deal with partial object occlusion and is
suitable for poorly textured objects.
https://hal.archives-ouvertes.fr/hal-01437638
Contributor : Équipe Gestionnaire Des Publications Si Liris <>
Submitted on : Tuesday, January 17, 2017 - 1:53:45 PM
Last modification on : Thursday, November 21, 2019 - 1:44:52 AM
Contributor : Équipe Gestionnaire Des Publications Si Liris <>
Submitted on : Tuesday, January 17, 2017 - 1:53:45 PM
Last modification on : Thursday, November 21, 2019 - 1:44:52 AM
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