DocumentCode :
1671062
Title :
Sensitivity of image-based and texture-based multi-view coding to model accuracy
Author :
Magnor, Marcus ; Girod, Bernd
Author_Institution :
Inf. Syst. Lab., Stanford Univ., CA, USA
Volume :
3
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
98
Abstract :
Multi-view image coding benefits from knowledge of the depicted scene´s 3D geometry. To exploit geometry information for compression, two different approaches can be distinguished. In texture-based coding, images are converted to texture maps prior to compression. In image-based predictive coding, geometry is used for disparity compensation and occlusion detection between images. Coding performance of both approaches depends on the accuracy of the available geometry model. Texture-based and image-based coding are compared with regard to the influence of geometry accuracy on coding efficiency. The results are theoretically explained. Experiments with natural as well as synthetic image sets show that texture-based coding is more sensitive to small geometry inaccuracies than image-based coding. For approximate geometry models, image-based coding performs best, while texture-based coding yields superior coding results if scene geometry is exactly known
Keywords :
computational geometry; data compression; image coding; image texture; prediction theory; 3D geometry; coding efficiency; disparity compensation; geometry accuracy; image compression; image-based predictive coding; model accuracy; multi-view image coding; occlusion detection; performance; texture maps; texture-based coding; Decoding; Image coding; Information geometry; Laboratories; Layout; Pixel; Predictive coding; Predictive models; Rendering (computer graphics); Solid modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
Type :
conf
DOI :
10.1109/ICIP.2001.958060
Filename :
958060
Link To Document :
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