A fast convex hull algorithm inspired by human visual perception

2018 ◽  
Vol 77 (23) ◽  
pp. 31221-31237 ◽  
Author(s):  
Runzong Liu ◽  
Yuan Yan Tang ◽  
Patrick P. K. Chan
Keyword(s):  
Visual Perception ◽  
Convex Hull ◽  
Human Visual Perception ◽  
Convex Hull Algorithm

A Randomized Parallel Three-Dimensional Convex Hull Algorithm for Coarse-Grained Multicomputers

1997 ◽  
Vol 30 (6) ◽  
pp. 547-558 ◽  
Author(s):  
F. Dehne ◽  
X. Deng ◽  
P. Dymond ◽  
A. Fabri ◽  
A. A. Khokhar
Keyword(s):  
Convex Hull ◽  
Three Dimensional ◽  
Coarse Grained ◽  
Convex Hull Algorithm

scholarly journals Improved Convex Hull Algorithm Applied to Body Size Measurements

2021 ◽  
Vol 1790 (1) ◽  
pp. 012089
Author(s):  
Fang Qi ◽  
Sun GuangWu ◽  
Chen Yu
Keyword(s):  
Body Size ◽  
Convex Hull ◽  
Convex Hull Algorithm

An improved line continuation model in human visual perception

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

scholarly journals Method for Vortex Shape Retrieval and Area Calculation Based on Convex Hull Algorithm

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 2706-2714
Author(s):  
Xu Wei ◽  
Jiyu Li ◽  
Bo Long ◽  
Xiaodan Hu ◽  
Han Wu ◽  
...  
Keyword(s):  
Convex Hull ◽  
Shape Retrieval ◽  
Convex Hull Algorithm

scholarly journals Waveguide combiners for mixed reality headsets: a nanophotonics design perspective

Nanophotonics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 41-74
Author(s):  
Bernard C. Kress ◽  
Ishan Chatterjee
Keyword(s):  
Visual Perception ◽  
Mixed Reality ◽  
Deep Understanding ◽  
Large Field ◽  
High Angular Resolution ◽  
List Type ◽  
Human Visual Perception ◽  
Perception System ◽  
Social Comfort ◽  
Hardware Architectures

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.

Social Attribution and Explanation

2017 ◽  
Author(s):  
Denis Hilton
Keyword(s):  
Visual Perception ◽  
Final Section ◽  
Higher Order ◽  
Situation Models ◽  
Causal Connection ◽  
Human Visual Perception ◽  
Social Attribution ◽  
Text Understanding ◽  
Causal Selection ◽  
Partial Correction

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.

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