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Geometry-based shading for shape depiction Enhancement,

Kolivand, H, Al-Rousan, R and Shahrizal Sunar, M (2017) Geometry-based shading for shape depiction Enhancement,. Multimedia Tools and Applications. ISSN 1380-7501

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Recent works on Non-Photorealistic Rendering (NPR) show that object shape enhancement requires sophisticated effects such as: surface details detection and stylized shading. To date, some rendering techniques have been proposed to overcome this issue, but most of which are limited to correlate shape enhancement functionalities to surface feature variations. Therefore, this problem still persists especially in NPR. This paper is an attempt to address this problem by presenting a new approach for enhancing shape depiction of 3D objects in NPR. We first introduce a tweakable shape descriptor that offers versatile func- tionalities for describing the salient features of 3D objects. Then to enhance the classical shading models, we propose a new technique called Geometry-based Shading. This tech- nique controls reflected lighting intensities based on local geometry. Our approach works without any constraint on the choice of material or illumination. We demonstrate results obtained with Blinn-Phong shading, Gooch shading, and cartoon shading. These results prove that our approach produces more satisfying results compared with the results of pre- vious shape depiction techniques. Finally, our approach runs on modern graphics hardware in real time, which works efficiently with interactive 3D visualization.

Item Type: Article
Additional Information: This is a post-peer-review, pre-copyedit version of an article published in Multimedia Tools and Applications. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11042-017-4486-3
Uncontrolled Keywords: 0803 Computer Software, 0805 Distributed Computing, 0806 Information Systems, 0801 Artificial Intelligence And Image Processing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science & Mathematics
Publisher: Springer Verlag
Date Deposited: 01 Mar 2018 10:17
Last Modified: 04 Sep 2021 03:08
DOI or ID number: 10.1007/s11042-017-4486-3
URI: https://researchonline.ljmu.ac.uk/id/eprint/8076
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