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Optical Engineering

Interactive optimization of photo composition with Gaussian mixture model on mobile platform
Author(s): Hachon Sung; Guntae Bae; Sunyoung Cho; Hyeran Byun
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Paper Abstract

A good photo is determined using various visual elements of photography and these elements have been implemented in mobile devices with functionalities including zooming, auto-focusing and auto-white-balancing. Although composition is an important element of a good photo and an interesting research topic, most composition-related functionalities have not been added to mobile devices. We propose a guide system for capturing good photos in mobile devices that considers composition elements. A photo composition mixture model (PCMM) is derived based on composition elements such as a Gaussian Mixture Model (GMM), and the best composition of current input is gradually determined by iterating the PCMM optimization. Experimental evaluations are conducted to show the usefulness of the proposed PCMM and its optimization performance. To show the efficiency of recomposition performance and speed, we compare our method with retargeting-based methods. By implementing our method in mobile devices, we show that our system offers valid user guidance for capturing a photo with good composition in realtime.

Paper Details

Date Published: 8 February 2012
PDF: 14 pages
Opt. Eng. 51(1) 017001 doi: 10.1117/1.OE.51.1.017001
Published in: Optical Engineering Volume 51, Issue 1
Show Author Affiliations
Hachon Sung, Yonsei Univ. (Korea, Republic of)
Guntae Bae, Yonsei Univ. (Korea, Republic of)
Sunyoung Cho, Yonsei Univ. (Korea, Republic of)
Hyeran Byun, Yonsei Univ. (Korea, Republic of)


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