Proc. IEEE Asilomar Conf. on Signals, Systems, and Computers,
vol. 2, pp. 1640-1644, Nov. 9-12, 2003, Pacific Grove, CA USA.
A Novel Gradient Induced Main Subject Segmentation Algorithm
for Digital Still Cameras
Brian L. Evans
Department of Electrical and Computer Engineering,
Engineering Science Building,
The University of Texas at Austin,
Austin, TX 78712-1084 USA
Research on Digital Still Cameras at UT Austin
When taking pictures, professional photographers employ a variety of
In automating these rules, it is often first necessary to detect
and segment the main subject.
We propose an detection and segmentation algorithm that leverages
the optics in a digital still camera.
Based on where the user points the camera, an auto-focus filter first puts
the main subject in focus and takes a picture.
Then, we open the shutter aperture to diffuse light from objects that are
out-of-focus, which blurs the background, and take a second picture.
Using the second picture, the resulting difference in the frequency content
of the main subject and the background image is then used by the proposed
algorithm to detect and segment the main subject.
The algorithm does not depend on prior knowledge of the indoor/outdoor
setting or scene content.
Algorithm complexity is similar to that of a 5 x 5 filter.
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