The way the human body is depicted in classical and modern paintings is relevant for art historical analyses. Each artist has certain themes and concerns, resulting in different poses being used more heavily than others. In this paper, we propose a computer vision pipeline to analyse human pose and representations in paintings, which can be used for specific artists or periods. Specifically, we combine two pose estimation approaches (OpenPose and DensePose, respectively) and introduce methods to deal with occlusion and perspective issues. For normalisation, we map the detected poses and contours to Leonardo da Vinci's Vitruvian Man, the classical depiction of body proportions. We propose a visualisation approach for illustrating the articulation of joints in a set of paintings. Combined with a hierarchical clustering of poses, our approach reveals common and uncommon poses used by artists. Our approach improves over purely skeleton based analyses of human body in paintings.
翻译:古典和现代绘画对人体的描述方式与艺术历史分析有关。 每个艺术家都有某些主题和关切,导致不同姿势的使用比其他艺术家要严重得多。 在本文中,我们提议建立一个计算机视觉管道,用于分析人的形象和绘画的表述,可用于特定的艺术家或时期。具体地说,我们将两种构成估计方法(分别为OpenPose和DensePose)结合起来,并引入处理包容和视角问题的方法。为了正常化,我们把所探测到的姿势和轮廓绘制成像给Leonardo da Vinci's Vitruvian Man,即人体比例的古典描述。我们提出一种视觉化方法,用于在一组绘画中展示联合的表达方式。结合了组合结构的分级组合,我们的方法揭示了艺术家使用的共同和不寻常的姿势。我们的方法改进了纯粹基于骨骼的人体绘画分析。