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

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 -

Paper - Poster - Code

Research on Digital Still Cameras at UT Austin


When taking pictures, professional photographers employ a variety of composition rules. 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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Last Updated 11/03/05.