Computer Vision Models to Categorize Art Collections According to the Visual Content: A New Approach to the Abstract Art of Antoni Tàpies

Leonardo ◽  
2019 ◽  
Vol 52 (3) ◽  
pp. 255-260 ◽  
Author(s):  
Pilar Rosado

This study uses computer vision models, which to some extent simulate the initial stages of human visual perception, to help categorize data in large sets of images of artworks by the artist Antoni Tàpies. The images have been analyzed on the basis of their compositional, chromatic and organizational characteristics, without textual notes, so that the analogies found may take us closer to, and help us to understand, the creator’s original values. The system as programmed can assist the specialist by establishing analogies between different artists or periods using the same criteria.

Author(s):  
Yung-Sheng Chen ◽  
Kun-Li Lin

Eye–hand coordination (EHC) is of great importance in the research areas of human visual perception, computer vision and robotic vision. A computer-using robot (CUBot) is designed for investigating the EHC mechanism and its implementation is presented in this paper. The CUBot possesses the ability of operating a computer with a mouse like a human being. Based on the three phases of people using computer with a mouse, i.e. watching the screen, recognizing the graphical objects on the screen as well as controlling the mouse to let the cursor approach to the target, our CUBot can also perceive information merely through its vision and control the mouse by its robotic hand without any physical data communication connected to the operated computer. The CUBot is mainly composed of “Mouse-Hand” for operating the mouse, “mind” for realizing the object perception, cursor tracking, and EHC. Two experiments used for testing the ability of our EHC algorithm and the perception of CUBot confirm the feasibility of the proposed approach.


1993 ◽  
Vol 26 (6) ◽  
pp. 825-842 ◽  
Author(s):  
Yung-Sheng Chen ◽  
Shih-Liang Chang ◽  
Wen-Hsing Hsu

Nanophotonics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 41-74
Author(s):  
Bernard C. Kress ◽  
Ishan Chatterjee

AbstractThis paper is a review and analysis of the various implementation architectures of diffractive waveguide combiners for augmented reality (AR), mixed reality (MR) headsets, and smart glasses. Extended reality (XR) is another acronym frequently used to refer to all variants across the MR spectrum. Such devices have the potential to revolutionize how we work, communicate, travel, learn, teach, shop, and are entertained. Already, market analysts show very optimistic expectations on return on investment in MR, for both enterprise and consumer applications. Hardware architectures and technologies for AR and MR have made tremendous progress over the past five years, fueled by recent investment hype in start-ups and accelerated mergers and acquisitions by larger corporations. In order to meet such high market expectations, several challenges must be addressed: first, cementing primary use cases for each specific market segment and, second, achieving greater MR performance out of increasingly size-, weight-, cost- and power-constrained hardware. One such crucial component is the optical combiner. Combiners are often considered as critical optical elements in MR headsets, as they are the direct window to both the digital content and the real world for the user’s eyes.Two main pillars defining the MR experience are comfort and immersion. Comfort comes in various forms: –wearable comfort—reducing weight and size, pushing back the center of gravity, addressing thermal issues, and so on–visual comfort—providing accurate and natural 3-dimensional cues over a large field of view and a high angular resolution–vestibular comfort—providing stable and realistic virtual overlays that spatially agree with the user’s motion–social comfort—allowing for true eye contact, in a socially acceptable form factor.Immersion can be defined as the multisensory perceptual experience (including audio, display, gestures, haptics) that conveys to the user a sense of realism and envelopment. In order to effectively address both comfort and immersion challenges through improved hardware architectures and software developments, a deep understanding of the specific features and limitations of the human visual perception system is required. We emphasize the need for a human-centric optical design process, which would allow for the most comfortable headset design (wearable, visual, vestibular, and social comfort) without compromising the user’s sense of immersion (display, sensing, and interaction). Matching the specifics of the display architecture to the human visual perception system is key to bound the constraints of the hardware allowing for headset development and mass production at reasonable costs, while providing a delightful experience to the end user.


Author(s):  
Denis Hilton

Attribution processes appear to be an integral part of human visual perception, as low-level inferences of causality and intentionality appear to be automatic and are supported by specific brain systems. However, higher-order attribution processes use information held in memory or made present at the time of judgment. While attribution processes about social objects are sometimes biased, there is scope for partial correction. This chapter reviews work on the generation, communication, and interpretation of complex explanations, with reference to explanation-based models of text understanding that result in situation models of narratives. It distinguishes between causal connection and causal selection, and suggests that a factor will be discounted if it is not perceived to be connected to the event and backgrounded if it is perceived to be causally connected to that event, but is not selected as relevant to an explanation. The final section focuses on how interpersonal explanation processes constrain causal selection.


2017 ◽  
Author(s):  
Jeremy Cole ◽  
David Reitter ◽  
Yanxi Liu

Most literature on symmetry perception has focused on bilateralreflection symmetry with some suggesting that it isthe only type of symmetry humans can perceive (Wilson &Wilkinson, 2002). Using image stimuli generated from themathematically well-defined seventeen wallpaper groups, thisstudy demonstrates that humans can discriminate various symmetriesfound in 2D wallpaper patterns (Liu, Hel-Or, Kaplan,Van Gool, et al., 2010). Furthermore, the results demonstratethe features which contribute to wallpaper pattern perception.All wallpaper groups but one were found to be reliably distinguishable(p < 0:05). Additionally, as wallpaper patterns canbe arranged in a hierarchy, we propose a metric to quantify thesimilarity of their perception using the shortest path in this hierarchy.This subgroup distance was found to be a factor in alikely model of pattern perception.


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