Abstract While lens flares are often undesired artifacts of the imaging process, they are also essential for increasing the level of realism in video games and serve as a powerful artistic tool for photography and filmography. For these reasons, computationally reproducing lens flares has always received special attention. Due to the cost of analytical ray tracing, existing solutions are unable to simultaneously achieve the performance needed for real-time environments and retain the ability to simulate arbitrarily complex ghost shapes. Although polynomial optics has been successfully used to increase the efficiency of ray tracing in multiple rendering areas, no complete and validated solution exists that correctly models all aspects of lens flares. This paper presents our polynomial optics-based method for efficiently and accurately ray tracing lens flare ghosts. Our approach successfully models the shape, energy absorption, chromatic effects, and blocking of lens flare rays by partitioning the input domain into local fitting zones. We demonstrate that our model provides a considerable speedup and high accuracy compared to the analytical approach and achieves better fitting speed, output quality, and rendering performance than the naïve application of polynomial optics. The source code for our implementation is available on GitHub .

Abstract With the recent progress made in areas such as head-mounted displays and vision-correcting devices, there is a growing interest in fast and personalized algorithms for simulating aberrated human vision. Existing vision-simulating approaches are generally hindered by the lack of personalization, computational cost of rendering, and limited types of supported aberrations. This paper presents a fast vision simulation method with interactive personalization capabilities for simulating arbitrary central and peripheral aberrations of the human eye. First, we describe a novel, neural network-based solution for efficiently estimating the physical structure of the simulated eye and calculating the necessary Zernike aberration coefficients for computing the point-spread functions with varying pupil sizes, focus distances, and incidence angles. Our new approach operates in the sub-second regime and produces highly accurate outputs, facilitating the interactive personalization of vision simulation. Next, we present an improved PSF interpolation method for an existing tiled PSF splatting algorithm for rendering. The proposed algorithm significantly improves the computational performance and memory efficiency of the previous approach, allowing the simulation of peripheral vision with arbitrary visual aberrations in low-latency applications. Following the description of our new techniques, we evaluate their performance characteristics and simulation accuracies on several different eye conditions and test scenarios and compare our results to several previous vision simulation algorithms.

The lens flare phenomenon is often an undesired artifact of the imaging process; however, it has become an important artistic tool in photography and cinematography as well as a highly impactful component for increasing the level of realism for computer-generated images. In this paper, we present a novel method for efficiently simulating the lens flares of optical camera systems in highly interactive environments. Recreating this effect in a physically correct way necessitates the use of ray tracing, which we made much more computationally efficient by using a tiled approach to rasterize the ghosts of the lens flare. One of the main drawbacks of the current state-of-the-art method is the huge pixel overdraw resulting from the large number of ghosts being rasterized individually onto the output image. The problem is made even worse when dense ray grids are utilized for improving the quality of the simulation. We overcome these limitations by collecting all the ray-traced ghost data into screen-aligned tiles and accumulating the per-pixel contributions in a single pass. We demonstrate that our tiled approach significantly outperforms the previous algorithm, scales much better with the number of flares rendered, and facilitates the efficient simulation of lens flares in real-time applications, while maintaining the physical correctness.

Disk B-spline curve provides an alternative shape modeling tool to standard control point based modeling techniques by extending control points to control disks, resulting in an easy and straightforward way of modeling regions or shapes with adjustable thickness. Due to this feature, disk B-spline curves are frequently applied in artistic shape modeling applications, such as brushstroke representation, calligraphy, and animation, but they are also suitable for engineering purposes. However, the boundary curves of the described shapes tend to have unintentional self-intersections or cusps, negatively affecting the usability and artistic value of the resulting shape and texture. In this paper, we introduce an iterative algorithm to give a solution to this problematic issue with the help of an approximating circle skinning method, while preserving the advantageous properties of the disk B-spline curves. Our method also results in smoother texturing of the shape around the more sharply curved sections.

Abstract Visual aberrations are the imperfections in human vision, which play an important role in our everyday lives. Existing algorithms to simulate such conditions are either not suited for low‐latency workloads or limit the kinds of supported aberrations. In this paper, we present a new simulation method that supports arbitrary visual aberrations and runs at interactive, near real‐time performance on commodity hardware. Furthermore, our method only requires a single set of on‐axis phase aberration coefficients as input and handles the dynamic change of pupil size and focus distance at runtime. We first describe a custom parametric eye model and parameter estimation method to find the physical properties of the simulated eye. Next, we talk about our parameter sampling strategy which we use with the estimated eye model to establish a coarse point‐spread function (PSF) grid. We also propose a GPU‐based interpolation scheme for the kernel grid which we use at runtime to obtain the final vision simulation by extending an existing tile‐based convolution approach. We showcase the capabilities of our eye estimation and rendering processes using several different eye conditions and provide the corresponding performance metrics to demonstrate the applicability of our method for interactive environments.