Styling Classification of Group Photos Fusing Head and Pose Features

Kai Wang, Congwei Guo, Zhuang Zhao, Yongzhen Ke, Shuai Yang
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引用次数: 0

Abstract

Group photo images are everywhere and vary greatly by the shooting scene. Compared with common images, the Image Aesthetic Quality Assessment (IAQI) of group photo pays more attention to the relevant characteristics of the main population. Still, the existing methods do not make further special research on group photos. Therefore, we propose a new concept of group photo styling based on analyzing group photos and photographic theory. Besides that, by comparing and analyzing many group photos, we classify the group photos into five categories. In this paper, the main factors of the head and pose are considered simultaneously, and the method of Group Photo Styling Classification (GPSC) can classify different group photos automatically. To verify the effectiveness of our method, we collected a Group Photo Styling Dataset (GPSD). The dataset contains 998 group photo images, and each image’s group photo styling category is marked. The experimental results on GPSD show that the fusion of head features and pose features can classify different group photos well. The accuracy of GPSC reaches 93.9%, much higher than the previous classification model.
融合头部和姿态特征的群像造型分类
集体照随处可见,不同的拍摄场景差别很大。与普通图像相比,集体照的图像审美质量评价(IAQI)更关注主体人群的相关特征。然而,现有的方法并没有对集体照片进行进一步的专门研究。因此,我们在分析集体照和摄影理论的基础上,提出了集体照造型的新概念。此外,通过对大量的集体照进行对比分析,我们将集体照分为五类。本文同时考虑了头部和姿态的主要影响因素,提出了一种基于GPSC的集体照样式分类方法,可以对不同的集体照进行自动分类。为了验证我们方法的有效性,我们收集了一个团体照片样式数据集(GPSD)。该数据集包含998张集体照图像,并标记了每个图像的集体照样式类别。GPSD的实验结果表明,融合头部特征和姿态特征可以很好地分类不同的群体照片。GPSC的准确率达到93.9%,大大高于以往的分类模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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