Gaussian Light Field: Estimation of Viewpoint-Dependent Blur for Optical See-Through Head-Mounted Displays

LFACon: Introducing Anglewise Attention to No-Reference Quality Assessment in Light Field Space

Light field imaging can capture both the intensity information and the direction information of light rays. It naturally enables a six-degrees-of-freedom viewing experience and deep user engagement in virtual reality. Compared to 2D image assessment, light field image quality assessment (LFIQA) needs to consider not only the image quality in the spatial domain but also the quality consistency in the angular domain. However, there is a lack of metrics to effectively reflect the angular consistency and thus the angular quality of a light field image (LFI). Furthermore, the existing LFIQA metrics suffer from high computational costs due to the excessive data volume of LFIs. In this paper, we propose a novel concept of "anglewise attention" by introducing a multihead self-attention mechanism to the angular domain of an LFl. This mechanism better reflects the LFI quality. In particular, we propose three new attention kernels, including anglewise self-attention, anglewise grid attention, and anglewise central attention. These attention kernels can realize angular self-attention, extract multiangled features globally or selectively, and reduce the computational cost of feature extraction. By effectively incorporating the proposed kernels, we further propose our light field attentional convolutional neural network (LFACon) as an LFIQA metric. Our experimental results show that the proposed LFACon metric significantly outperforms the state-of-the-art LFIQA metrics. For the majority of distortion types, LFACon attains the best performance with lower complexity and less computational time.

Neural distortion fields for spatial calibration of wide field-of-view near-eye displays

We propose a spatial calibration method for wide field-of-view (FoV) near-eye displays (NEDs) with complex image distortions. Image distortions in NEDs can destroy the reality of the virtual object and cause sickness. To achieve distortion-free images in NEDs, it is necessary to establish a pixel-by-pixel correspondence between the viewpoint and the displayed image. Designing compact and wide-FoV NEDs requires complex optical designs. In such designs, the displayed images are subject to gaze-contingent, non-linear geometric distortions, which explicit geometric models can be difficult to represent or computationally intensive to optimize. To solve these problems, we propose neural distortion field (NDF), a fully-connected deep neural network that implicitly represents display surfaces complexly distorted in spaces. NDF takes spatial position and gaze direction as input and outputs the display pixel coordinate and its intensity as perceived in the input gaze direction. We synthesize the distortion map from a novel viewpoint by querying points on the ray from the viewpoint and computing a weighted sum to project output display coordinates into an image. Experiments showed that NDF calibrates an augmented reality NED with 90° FoV with about 3.23 pixel (5.8 arcmin) median error using only 8 training viewpoints. Additionally, we confirmed that NDF calibrates more accurately than the non-linear polynomial fitting, especially around the center of the FoV.

Depth of Field Rendering Using Multilayer-Neighborhood Optimization

Depth of field (DOF) is utilized widely to deliver artistic effects in photography. However, existing post-processing techniques for rendering DOF effects introduce visual artifacts such as color leakage, blurring discontinuity, and the partial occlusion problems which limit the application of DOF. Traditionally, occluded pixels are ignored or not well estimated although they might make key contributions to images. In this paper, we propose a new filtering approach which takes approximated occluded pixels into account to synthesize the DOF effects for images. In our approach, images are separated into different layers based on depth. Besides, we utilize adaptive PatchMatch method to estimate the intensities of occluded pixels, especially in the background region. We again propose a new multilayer-neighborhood optimization to estimate occluded pixels contributions and render the images. Finally, we apply gathering filter to achieve the rendered images with elite DOF effects. Multiple experiments have shown that our approach can handle color leakage, blurring discontinuity and partial occlusion problem while providing high-quality DOF rendering effects.

Ambient light robust gamut mapping for optical see-through displays

An optical see-through (OST) display is affected more severely by ambient light than any other type of displays when placed in an outdoor environment with bright illuminance because of its transparency and thus, its inherent color distortion can worsen. It is hard to directly apply existing gamut mapping methods to an OST display because of its morphological gamut characteristic and the effect of ambient light. In this paper, we propose a new robust gamut mapping method which works against bright ambient light. The process is divided into two steps: lightness mapping (LM) and chroma reproduction. LM aligns the lightness level of sRGB gamut with OST gamut and partitions the region of OST gamut based on the relative size of the sRGB gamut and its lightness value. The second step (chroma reproduction) determines an appropriate chroma reproduction method (gamut compression or extension) and a proper direction for gamut mapping based on the characteristics of each region in order to minimize the effects of ambient light. The quality of color reproduction is qualitatively and quantitatively evaluated based on accurate measurements of the displayed colors. It has been experimentally confirmed that the proposed gamut mapping method can reduce color distortion more than the existing parametric gamut mapping algorithms.

Revisiting Trends in Augmented Reality Research: A Review of the 2nd Decade of ISMAR (2008-2017)

In 2008, Zhou et al. presented a survey paper summarizing the previous ten years of ISMAR publications, which provided invaluable insights into the research challenges and trends associated with that time period. Ten years later, we review the research that has been presented at ISMAR conferences since the survey of Zhou et al., at a time when both academia and the AR industry are enjoying dramatic technological changes. Here we consider the research results and trends of the last decade of ISMAR by carefully reviewing the ISMAR publications from the period of 2008-2017, in the context of the first ten years. The numbers of papers for different research topics and their impacts by citations were analyzed while reviewing them-which reveals that there is a sharp increase in AR evaluation and rendering research. Based on this review we offer some observations related to potential future research areas or trends, which could be helpful to AR researchers and industry members looking ahead.

A Survey of Calibration Methods for Optical See-Through Head-Mounted Displays

Optical see-through head-mounted displays (OST HMDs) are a major output medium for Augmented Reality, which have seen significant growth in popularity and usage among the general public due to the growing release of consumer-oriented models, such as the Microsoft Hololens. Unlike Virtual Reality headsets, OST HMDs inherently support the addition of computer-generated graphics directly into the light path between a user's eyes and their view of the physical world. As with most Augmented and Virtual Reality systems, the physical position of an OST HMD is typically determined by an external or embedded 6-Degree-of-Freedom tracking system. However, in order to properly render virtual objects, which are perceived as spatially aligned with the physical environment, it is also necessary to accurately measure the position of the user's eyes within the tracking system's coordinate frame. For over 20 years, researchers have proposed various calibration methods to determine this needed eye position. However, to date, there has not been a comprehensive overview of these procedures and their requirements. Hence, this paper surveys the field of calibration methods for OST HMDs. Specifically, it provides insights into the fundamentals of calibration techniques, and presents an overview of both manual and automatic approaches, as well as evaluation methods and metrics. Finally, it also identifies opportunities for future research.

Comparison of optical see-through head-mounted displays for surgical interventions with object-anchored 2D-display

PURPOSE

Optical see-through head-mounted displays (OST-HMD) feature an unhindered and instantaneous view of the surgery site and can enable a mixed reality experience for surgeons during procedures. In this paper, we present a systematic approach to identify the criteria for evaluation of OST-HMD technologies for specific clinical scenarios, which benefit from using an object-anchored 2D-display visualizing medical information.

METHODS

Criteria for evaluating the performance of OST-HMDs for visualization of medical information and its usage are identified and proposed. These include text readability, contrast perception, task load, frame rate, and system lag. We choose to compare three commercially available OST-HMDs, which are representatives of currently available head-mounted display technologies. A multi-user study and an offline experiment are conducted to evaluate their performance.

RESULTS

Statistical analysis demonstrates that Microsoft HoloLens performs best among the three tested OST-HMDs, in terms of contrast perception, task load, and frame rate, while ODG R-7 offers similar text readability. The integration of indoor localization and fiducial tracking on the HoloLens provides significantly less system lag in a relatively motionless scenario.

CONCLUSIONS

With ever more OST-HMDs appearing on the market, the proposed criteria could be used in the evaluation of their suitability for mixed reality surgical intervention. Currently, Microsoft HoloLens may be more suitable than ODG R-7 and Epson Moverio BT-200 for clinical usability in terms of the evaluated criteria. To the best of our knowledge, this is the first paper that presents a methodology and conducts experiments to evaluate and compare OST-HMDs for their use as object-anchored 2D-display during interventions.