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 lter, 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 di used light. The segmentation utilizes the di erence in frequency content b e t ween 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 rst de ne 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.
In another work a digital camera automatically detects the main subject and shifts the image to place it on the Rule of Thirds lines and blurs the background REF .
Unsupervised automation of photographic composition rules in digital still cameras
IS&T/SPIE Electronic Imaging
Engineering Computer Science