TY - GEN
T1 - Texture analysis and repacking for improved storage efficiency
AU - Odaker, Thomas
AU - Wiedemann, Markus
AU - Anthes, Christoph
AU - Kranzlmüller, Dieter
N1 - Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016/11/2
Y1 - 2016/11/2
N2 - Textures are widely used in modern computer graphics. Their size, however, is often a limiting factor. Considering the widespread adaptation of mobile virtual and augmented reality applications, efficient storage of textures has become an important factor. We present an approach to analyse textures of a given mesh and compute a new set of textures with the goal of improving storage efficiency and reducing memory requirements. During this process the texture coordinates of the mesh are updated as required. Textures are analysed based on the UV-coordinates of one or more meshes and deconstructed into per-triangle textures. These are further analysed to detect single coloured as well as identical pertriangle textures. Our approach aims to remove these redundancies in order to reduce the amount of memory required to store the texture data. After this analysis, the per-triangle textures are compiled into a new set of texture images of user defined size. Our algorithm aims to pack texture data as tightly as possible in order to reduce the memory requirements.
AB - Textures are widely used in modern computer graphics. Their size, however, is often a limiting factor. Considering the widespread adaptation of mobile virtual and augmented reality applications, efficient storage of textures has become an important factor. We present an approach to analyse textures of a given mesh and compute a new set of textures with the goal of improving storage efficiency and reducing memory requirements. During this process the texture coordinates of the mesh are updated as required. Textures are analysed based on the UV-coordinates of one or more meshes and deconstructed into per-triangle textures. These are further analysed to detect single coloured as well as identical pertriangle textures. Our approach aims to remove these redundancies in order to reduce the amount of memory required to store the texture data. After this analysis, the per-triangle textures are compiled into a new set of texture images of user defined size. Our algorithm aims to pack texture data as tightly as possible in order to reduce the memory requirements.
KW - Texture;texture optimization;texture packing
UR - http://www.scopus.com/inward/record.url?scp=84998978785&partnerID=8YFLogxK
U2 - 10.1145/2993369.2996332
DO - 10.1145/2993369.2996332
M3 - Conference contribution
T3 - Proceedings of the ACM Symposium on Virtual Reality Software and Technology, VRST
SP - 361
EP - 362
BT - Proceedings - VRST 2016
A2 - Spencer, Stephen N.
PB - Association for Computing Machinery
T2 - 22nd ACM Conference on Virtual Reality Software and Technology, VRST 2016
Y2 - 2 November 2016 through 4 November 2016
ER -