Proc. IS&T/SPIE Conf. on Sensors, Color, Cameras, and Systems
for Digital Photography,
Jan. 18-22, 2004, vol. 5301, pp. 364-373, San Jose, CA USA
Unsupervised Automation of Photographic Composition Rules
in Digital Still Cameras
Serene Banerjee
and
Brian L. Evans
Department of Electrical and Computer Engineering,
Engineering Science Building,
The University of Texas at Austin,
Austin, TX 78712-1084 USA
serene@ece.utexas.edu -
bevans@ece.utexas.edu
Draft of Paper -
Talk
Abstract
When taking pictures, professional photographers apply photographic
composition rules, e.g. rule of thirds.
The rule of thirds says to place the main subject's center at one of four
places: at 1/3 or 2/3 of the picture width from left edge, and 1/3 or 2/3 of
the picture height from the top edge.
This paper develops low-complexity unsupervised methods for digital
still cameras to (1) segment the main subject and (2) realize the
rule-of-thirds.
The main subject segmentation method uses the auto-focus filter,
opens the shutter aperture fully, and segments the resulting image.
These camera settings place the main subject in focus and blur the rest
of the image by diffused light.
The segmentation utilizes the difference in frequency content between
the main subject and blurred background.
The segmentation does not depend on prior knowledge of the indoor/outdoor
setting or scene content.
The rule-of-thirds method moves the centroid of the main subject to the
closest of the four rule-of-thirds locations.
We first define an objective function that measures how close the main
subject placement obeys the rule-of-thirds, and then reposition the main
subject in order to optimize the objective function.
For multiple main subjects, the proposed algorithm could be extended to use
rule-of-triangles by adding an appropriate constraint.
Questions
The following questions and comments were made by those attending
the presentation:
- Why did you use a 3x3 filter for blurring -- you could use a 5x5 or 7x7
for more blur?
- When you shift pixels to generate a picture, following the
rule-of-thirds, wouldn't it be better to have a wide angle camera, and
capture more surrounding? This way even after the pixels are shifted, the
borders will still have good data.
- Did you perform any subjective testing to see which of the pictures
generated by the algorithm were more appealing to the user?
- In future would you do any scene analysis to see if the main subject is
moving, before introducing linear blur?
- One can see that the segmentation is not perfect, but I would take it
for the lower complexity.
- I can see how segmenting the main subject would be good for constrained
image transmission, one can spend more bits where the main subject is
located.
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