Abstract
Humans have the ability to perceive kinetic depth effects, i.e., to perceived 3D shapes from 2D projections of rotating 3D objects. This process is based on a variety of visual cues such as lighting and shading effects. However, when such cues are weak or missing, perception can become faulty, as demonstrated by the famous silhouette illusion example of the spinning dancer. Inspired by this, we establish objective and subjective evaluation models of rotated 3D objects by taking their projected 2D images as input. We investigate five different cues: ambient luminance, shading, rotation speed, perspective, and color difference between the objects and background. In the objective evaluation model, we first apply 3D reconstruction algorithms to obtain an objective reconstruction quality metric, and then use quadratic stepwise regression analysis to determine weights of depth cues to represent the reconstruction quality. In the subjective evaluation model, we use a comprehensive user study to reveal correlations with reaction time and accuracy, rotation speed, and perspective. The two evaluation models are generally consistent, and potentially of benefit to inter-disciplinary research into visual perception and 3D reconstruction.
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Acknowledgements
This work was supported by Tianjin NSF (Nos. 18JCYBJC41300 and 18ZXZNGX00110), National Natural Science Foundation of China (No. 61972216), and the Open Project Program of the State Key Laboratory of Virtual Reality Technology and Systems, Beihang University (No. VRLAB2019B04).
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Meng-Yao Cui is currently an undergraduate at Nankai University, majoring in computer science and minoring in psychology. Her research interests include visual perception and computing, human–computer interaction, and machine learning.
Shao-Ping Lu is an associate professor of computer science at Nankai University, Tianjin, China. He has been a senior postdoctoral researcher at Vrije Universiteit Brussel. He received his Ph.D. degree in 2012 from Tsinghua University, China. He also spent two years on high-performance SOC/ASIC design in industry in Shanghai. His research interests lie primarily at the intersections of visual computing, with particular focus on 3D video processing, computational photography, visual scene analysis, and machine learning.
Miao Wang is an assistant professor with the State Key Laboratory of Virtual Reality Technology and Systems, the Research Institute for Frontier Science, Beihang University, and Peng Cheng Laboratory, China. He received his Ph.D. degree from Tsinghua University in 2016. During 2013–2014, he visited the Visual Computing Group in Cardiff University as a joint Ph.D. student. In 2016–2018, he worked as a postdoctoral researcher at Tsinghua University. His research interests lie in virtual reality and computer graphics, with a particular focus on content creation for virtual reality.
Yong-Liang Yang received his Ph.D. degree in computer science from Tsinghua University in 2009. He worked as a postdoctoral fellow and research scientist in King Abdullah University of Science and Technology from 2009 to 2014. He is currently a senior lecturer (associate professor) in the Department of Computer Science, University of Bath. His research interests include geometric modeling, computational design, interactive techniques, and applied machine learning.
Yu-Kun Lai received his bachelor and Ph.D. degrees in computer science from Tsinghua University, in 2003 and 2008, respectively. He is currently a reader in the School of Computer Science & Informatics, Cardiff University. His research interests include computer graphics, computer vision, geometry processing, and image processing.
Paul L. Rosin is a professor in the School of Computer Science & Informatics, Cardiff University. His research interests include the representation, segmentation, and grouping of curves, knowledgebased vision systems, early image representations, low level image processing, machine vision approaches to remote sensing, methods for evaluation of approximation algorithms, medical and biological image analysis, mesh processing, non-photorealistic rendering, and the analysis of shape in art and architecture.
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Cui, MY., Lu, SP., Wang, M. et al. 3D computational modeling and perceptual analysis of kinetic depth effects. Comp. Visual Media 6, 265–277 (2020). https://doi.org/10.1007/s41095-020-0180-x
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DOI: https://doi.org/10.1007/s41095-020-0180-x