Elimination of artifacts due to occlusion and discretization problems in image space blurring techniques

Authors:
Brian A. Barsky;Michael J. Tobias;Derrick P. Chu;Daniel R. Horn
Affiliations:
Computer Science Division, University of California, Berkeley, CA and School of Optometry, University of California, Berkeley, CA;Computer Science Division, University of California, Berkeley, CA;Computer Science Division, University of California, Berkeley, CA and Computer Science Department, University of California, Los Angeles, CA;Computer Science Division, University of California, Berkeley, CA
Venue:
Graphical Models - Special issue: Vision and computer graphics
Year:
2005

Citing 13
Cited 6

Stochastic sampling in computer graphics

ACM Transactions on Graphics (TOG)
A Computational Approach to Edge Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
The rendering equation

SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
A realistic camera model for computer graphics

SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
An image-based model for realistic lens systems in interactive computer graphics

Proceedings of the conference on Graphics interface '97
Statistically optimized sampling for distributed ray tracing

SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Antialiasing through stochastic sampling

SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Dynamically reparameterized light fields

Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Synthetic Image Generation with a Lens and Aperture Camera Model

ACM Transactions on Graphics (TOG)
Distributed ray tracing

SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Vision-realistic rendering: simulation of the scanned foveal image from wavefront data of human subjects

APGV '04 Proceedings of the 1st Symposium on Applied perception in graphics and visualization
Camera models and optical systems used in computer graphics: part I, object-based techniques

ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartIII
Camera models and optical systems used in computer graphics: part II, image-based techniques

ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartIII

Algorithms for rendering depth of field effects in computer graphics

ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
Depth of field postprocessing for layered scenes using constant-time rectangle spreading

Proceedings of Graphics Interface 2009
Depth-of-field rendering with multiview synthesis

ACM SIGGRAPH Asia 2009 papers
Real-time lens blur effects and focus control

ACM SIGGRAPH 2010 papers
An algorithm for rendering generalized depth of field effects based on simulated heat diffusion

ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part III
Layered depth-of-field rendering using color spreading

Proceedings of the 12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry

Quantified Score

Hi-index	0.00

Visualization

Abstract

Traditional computer graphics methods render images that appear sharp at all depths. Adding blur can add realism to a scene, provide a sense of scale, and draw a viewer's attention to a particular region of a scene. Our image-based blur algorithm needs to distinguish whether a portion of an image is either from a single object or is part of more than one object. This motivates two approaches to identify objects after an image has been rendered. We illustrate how these techniques can be used in conjunction with our image space method to add blur to a scene.