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首页> 外文期刊>Journal of Imaging Science and Technology >Focusness Extraction from Images for Automatic Camera Control by Measuring Objectness
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Focusness Extraction from Images for Automatic Camera Control by Measuring Objectness

机译:从图像中提取聚焦度,以通过测量物体的物体来自动控制相机

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摘要

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, the authors compare the values between focusness and saliency maps. Theyevaluate the focusness of 80 images in an image evaluation experiment with 20 observers. Saliency maps are calculated using six conventional algorithms. They show that the individual variations of focusness are insignificant in images that include only one major object. Furthermore, the authorsapply a GIST feature to the saliency method by using a center‐surround histogram and extract focusness from images with high accuracy.
机译:当前的数码相机具有各种自动控制系统。在自动照相机系统中,从图像中提取聚焦是非常重要的问题。即使对于业余摄影师来说,自动提取主要主题也使拍摄照片变得非常容易。提出了通过视觉显着性来评估聚焦性的方法,这些方法假定显着性高的区域也具有高聚焦性。但是,重点和显着性之间存在各种差异。在这项研究中,作者比较了聚焦图和显着图之间的值。在具有20位观察者的图像评估实验中,他们评估了80张图像的聚焦度。使用六种常规算法计算显着性图。他们表明,在仅包含一个主要对象的图像中,焦点的个体变化微不足道。此外,作者通过使用中心周围的直方图将GIST功能应用于显着性方法,并从图像中高精度提取聚焦。

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