Focusness Extraction from Images for Automatic Camera Control by Measuring Objectness

Satomi Tanaka, Kaori Kiyomitsu, Masanori Maki, Akihiro Kakinuma, Naohiro Kamijo, Hiroshi Takahashi and Norimichi Tsumura

JIST 2017 (accepted)

Abstract
Current digital cameras have various automatic control systems. In automatic camera systems, extracting focusness from an image is a very important problem. Automatic extraction of the main subject makes taking photos very easy, even for an amateur photographer. Methods have been proposed to evaluate focusness by visual saliency, which assume that an area with high saliency also has high focusness. However, various differences exist between focusness and saliency. In this study, we compare the values between focusness and saliency maps. We evaluate the focusness of 80 images in an image evaluation experiment with 20 observers. Saliency maps are calculated using six conventional algorithms. We show that the individual variations of focusness are very few in images that include only one major object. Furthermore, we apply a GIST feature to the saliency method by using a center-surround histogram and extract focusness from images with high accuracy.

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