Can You All Look Here? Towards Determining Gaze Uniformity In Group Images

Omkar N. Kulkarni, Vikram Patil, Shivam B. Parikh, Shashank Arora, P. Atrey
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引用次数: 4

Abstract

Since the advent of the smartphone, the number of group images taken every day is rising exponentially. The photographers' struggle is to make sure everyone looks at the camera while taking the picture. More specifically, in a group image, if everybody is not looking in the same direction, then the image's aesthetic quality and utility are depreciated. The photographer usually discards the image, and then subsequently, several images are taken to mitigate this issue. Usually, users have to manually check if the image is uniformly gazed, which is tedious and time-consuming. This paper proposes a method for classifying a given group image as uniformly gazed or nonuniformly gazed by calculating the Gaze Uniformity Index. We evaluate the proposed method on a subset of the ‘Images of Groups' dataset. The proposed method achieved an accuracy of 67%.
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你们能看这里吗?群体图像凝视均匀性的确定
自从智能手机问世以来,每天拍摄的集体照片数量呈指数级增长。摄影师的努力是确保每个人在拍照时都看着相机。更具体地说,在一个群体形象中,如果每个人都没有朝同一个方向看,那么形象的审美质量和效用就会贬值。摄影师通常丢弃图像,然后随后拍摄几张图像以减轻这个问题。通常,用户必须手动检查图像是否均匀凝视,这是繁琐且耗时的。本文提出了一种通过计算注视均匀指数来对给定图像进行均匀注视和非均匀注视分类的方法。我们在“组的图像”数据集的一个子集上评估了所提出的方法。该方法的准确率为67%。
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