Creating high fidelity 360° virtual reality with high dynamic range spherical panorama images

2019 ◽  
Vol 9 (1) ◽  
pp. 73-109
Author(s):  
Zi Siang See ◽  
Lizbeth Goodman ◽  
Craig Hight ◽  
Mohd Shahrizal Sunar ◽  
Arindam Dey ◽  
...  

Abstract This research explores the development of a novel method and apparatus for creating spherical panoramas enhanced with high dynamic range (HDR) for high fidelity Virtual Reality 360 degree (VR360) user experiences. A VR360 interactive panorama presentation using spherical panoramas can provide virtual interactivity and wider viewing coverage; with three degrees of freedom, users can look around in multiple directions within the VR360 experiences, gaining the sense of being in control of their own engagement. This degree of freedom is facilitated by the use of mobile displays or head-mount-devices. However, in terms of image reproduction, the exposure range can be a major difficulty in reproducing a high contrast real-world scene. Imaging variables caused by difficulties and obstacles can occur during the production process of spherical panorama facilitated with HDR. This may result in inaccurate image reproduction for location-based subjects, which will in turn result in a poor VR360 user experience. In this article we describe a HDR spherical panorama reproduction approach (workflow and best practice) which can shorten the production processes, and reduce imaging variables, and technical obstacles and issues to a minimum. This leads to improved photographic image reproduction with fewer visual abnormalities for VR360 experiences, which can be adaptable into a wide range of interactive design applications. We describe the process in detail and also report on a user study that shows the proposed approach creates images which viewers prefer, on the whole, to those created using more complicated HDR methods, or to those created without the use of HDR at all.

2007 ◽  
Vol 16 (1) ◽  
pp. 119-122 ◽  
Author(s):  
Patrick Ledda

In the natural world, the human eye is confronted with a wide range of colors and luminances. A surface lit by moonlight might have a luminance level of around 10−3 cd/m2, while surfaces lit during a sunny day could reach values larger than 105 cd/m2. A good quality CRT (cathode ray tube) or LCD (liquid crystal display) monitor is only able to achieve a maximum luminance of around 200 to 300 cd/m2 and a contrast ratio of not more than two orders of magnitude. In this context the contrast ratio or dynamic range is defined as the ratio of the highest to the lowest luminance. We call high dynamic range (HDR) images, those images (or scenes) in which the contrast ratio is larger than what a display can reproduce. In practice, any scene that contains some sort of light source and shadows is HDR. The main problem with HDR images is that they cannot be displayed, therefore although methods to create them do exist (by taking multiple photographs at different exposure times or using computer graphics 3D software for example) it is not possible to see both bright and dark areas simultaneously. (See Figure 1.) There is data that suggests that our eyes can see detail at any given adaptation level within a contrast of 10,000:1 between the brightest and darkest regions of a scene. Therefore an ideal display should be able to reproduce this range. In this review, we present two high dynamic range displays developed by Brightside Technologies (formerly Sunnybrook Technologies) which are capable, for the first time, of linearly displaying high contrast images. These displays are of great use for both researchers in the vision/graphics/VR/medical fields as well as professionals in the VFX/gaming/architectural industry.


2021 ◽  
Vol 2021 (29) ◽  
pp. 184-187
Author(s):  
Shi Xinye ◽  
Zhu Yuechen ◽  
Ming Ronnier Luo

An experiment was carried out to investigate the change of color appearance for 13 surface stimuli viewed under a wide range of illuminance levels (15-32000 lux) using asymmetrical matching method. Addition to the above, in the visual field, observers viewed colours in a dark (10 lux) and a bright (200000 lux) illuminance level at the same time to simulate HDR viewing condition. The results were used to understand the relationship between the color changes under HDR conditions, to generate a corresponding color dataset and to verify color appearance model, such as CIECAM16.


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