Using Value Images to Adjust Intensity in 3D Renderings and Photographs Reynold J. Bailey, Cindy M. Grimm. Goal. Exposition. Exposition (cont’d). Input: Original intensity image . Target intensity image (i.e. a value sketch). Pre-processing:
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Using Value Images to Adjust Intensity in 3D Renderings and Photographs
Reynold J. Bailey, Cindy M. Grimm
Technique for manipulating the intensity values in a 3D computer generated image or photograph.
Artists often make value sketches of a scene before beginning the final painting.
Note: The value sketch for a given rendering can be created by using a 2D paint program or by using traditional art media. For the examples presented here, we avoid the problem of aligning the value image with the original image by using a 2D paint program to create a layer directly on top of the original image.
Our system uses gradient descent to find a Value Mapping Function :
pixels (x,y) is minimized.
i.e. The absolute lighting in the resulting image corresponds to that of .
The relative lighting of the original image is preserved.
i.e. is monotonically increasing.
Contrast in the resulting image is maximized.
i.e. The slope of is maximized.
During the optimization process, a weighted sum of three error functions (corresponding to the 3 desired properties of V) is evaluated.
In general, it is not possible to match the value image exactly. One approach is to divide the image into regions that have similar value tones, and find a map that is ideal for each region.
Photographers and computer animators on the other hand, do not have the luxury of changing the tone values of a rendering to create the image they want.
A piece-wise linear function is used to represent .
Current / Future Work
We present an alternative method for adjusting a 3D computer generated image or photograph based on a user provided value sketch.
Other image segmentation techniques that allow for finer control are being explored.
Value Mapping Function
Note: For this example, the same weights were used for each segment. This causes the results for some segments to be closer to the target values than others. Evidence of this can be seen on the forehead where the lightest target area is not the lightest area in the result.
We are currently trying to develop techniques that analyze the image and automatically generate weights for each segment.
Automatic lighting design using a perceptual quality metric,
Shacked et al. 2001
A user interface for interactive cinematic shadow design,
Pellacini et al. 2002
Local illumination environments for direct lighting acceleration,
Fernandez et al. 2002
The lit sphere,
Sloan et al. 2001
(colored for illustration purposes)
Using texture synthesis for non-photorealistic shading from paint samples,
Kulla et al. 2001
Interactive technical illustration,
Gooch et al. 1999
A tone mapping algorithm for high contrast images,