Abstract High dynamic range (HDR) imaging provides the capability of handling real world lighting as opposed to traditional low (LDR) which struggles accurately represent images with higher range. However, most content is still available only in LDR. This paper presents a method for generating HDR from LDR based on deep Convolutional Neural Networks (CNNs) termed ExpandNet. ExpandNet accepts input and generates an expanded end‐to‐end fashion. The model attempts reconstruct missing...

Abstract Sheet metal stamping is widely used for high-volume production. Despite the wide adoption, it can lead to defects in manufactured components, making their quality unacceptable. Because of variety that occur on final product, human inspectors are frequently employed detect them. However, they be unreliable and costly, particularly at speeds match rate. In this paper, we propose an automatic inspection framework process based computer vision deep learning techniques. The low cost,...

Recently, Deep Learning-based methods for inverse tone mapping standard dynamic range (SDR) images to obtain high (HDR) have become very popular. These manage fill over-exposed areas convincingly both in terms of details and range. To be effective, deep learning-based need learn from large datasets transfer this knowledge the network weights. In work, we tackle problem a completely different perspective. What can single SDR 8-bit video? With presented self-supervised approach, show that,...

In this paper we present a new technique for the display of High Dynamic Range (HDR) images on Low (LDR) displays. The described process has three stages. First, input image is segmented into luminance zones. Second, tone mapping operator (TMO) that performs better in each zone automatically selected. Finally, resulting (TM) outputs are merged, generating final LDR output image. To establish TMO conducted preliminary psychophysical experiment using set HDR and six different TMOs. We...

Sky illumination is responsible for much of the lighting in a virtual environment. A machine-learning-based approach can compactly represent sky from both existing analytic models and captured environment maps. The proposed approximate at significantly reduced memory cost enable smooth transitions to be created small set maps discrete times day. author's results demonstrate accuracy close ground truth analytical capture-based methods. has low runtime overhead, so it used as generic offline...

Childhood obesity is a major problem in most developed countries, with significant negative impacts on children's health. A suggested method for reducing obesity, especially children, are serious games. These could promote healthy eating and increased physical activity. Ideally, they should also increase energy expenditure during play, not be sedentary experience. In the preliminary work described here, we produced demonstration game designed to combat childhood obesity. All user interaction...

Abstract Maximizing performance for rendered content requires making compromises on quality parameters depending the computational resources available . Yet, it is currently unclear which best maximize perceived quality. This work investigates across budgets primary spatiotemporal of resolution and frame rate. Three experiments are conducted. Experiment 1 (n = 26) shows that participants prefer fixed rates 60 frames per second (fps) at lower resolutions over 30 fps higher resolutions. 2 24)...

Inverse Tone Mapping (ITM) methods attempt to reconstruct High Dynamic Range (HDR) information from Low (LDR) image content. The dynamic range of well-exposed areas must be expanded and any missing due over/under-exposure recovered (hallucinated). majority focus on the former are relatively successful, while most attempts latter not sufficient quality, even ones based Convolutional Neural Networks (CNNs). A major factor for reduced inpainting quality in some works is choice loss function....

We present a fitted model of sky dome radiance and attenuation for realistic terrestrial atmospheres. Using scatterer distribution data from atmospheric measurement data, our considerably improves on the visual realism existing analytical clear models, as well interactive methods that are based approximating light transport. also provide features not found in models so far: patterns post-sunset conditions, in-scattered values finite viewing distances, an observer altitude resolved includes...

Virtual environments (VEs) grant the ability to experience real-world scenarios, such as driving, in a virtual, safe, and reproducible context. However, order achieve their full potential, fidelity of VE must provide confidence that it replicates perception experience. The computational cost simulating visuals accurately means compromises be made. In this paper, subjective evaluation driving at different quality settings is presented. Participants (n = 44) were driven around real world...

Detecting rare and costly defects, such as necks splits in sheet metal stamping, remains challenging for deep learning models due to low failure rates entailing few available samples train on. Synthetic images provide a simulated alternative; however, the two main current approaches have limitations generating split defect images. Image synthesis-based generate implausible training data, while physics-based are computationally expensive lack diversity required. To address this, we present...

Recently, there has been a significant progress in the research and development of high dynamic range (HDR) video technology state-of-the-art pipelines are able to offer higher bit depth support capture, store, encode, display HDR content. In this paper, we introduce novel compression algorithm, which uses perceptually uniform color opponent space, perceptual transfer function encode scene, error minimization scheme for accurate chroma reproduction. The proposed algorithm was objectively...

Virtual Environments (VEs) provide the opportunity to simulate a wide range of applications, from training entertainment, in safe and controlled manner. For applications which require realistic representations real world environments, VEs need multiple, physically accurate sensory stimuli. However, simulating all senses that comprise human system (HSS) is task requires significant computational resources. Since it intractable deliver at highest quality, we propose resource distribution...

In this paper we present an efficient method for supporting image based lighting (IBL) bidirectional methods. This improves both sampling of the environment, and detection important regions scene, such as windows doors. These parts scene often have a small area proportional to that entire so paths which pass through them are generated with low probability. The proposed in efficiency, by taking into account view importance, modifies distribution use light transport information from camera....

Abstract Rendering using physically based methods requires substantial computational resources. Most that are use straightforward techniques may excessively compute certain types of light transport, while ignoring more important ones. Importance sampling is an effective and commonly used technique to reduce variance in such methods. current approaches for rendering on Monte Carlo sample the BRDF cosine term, but unable indirect illumination as this term being computed. Knowledge incoming can...

A number of novel imaging technologies have been gaining popularity over the past few years. Foremost among these are stereoscopy and high dynamic range (HDR) Imaging. While a large body research has looked into each independently, very little work attempted to combine them. This is mostly due current limitations in capture display. In this article, we mitigate problems capturing Stereoscopic HDR (SHDR) that would potentially require two cameras, by an LDR pair using it generate 3D...

Abstract A major challenge in generating high‐fidelity virtual environments (VEs) is to be able provide realism at interactive rates. The simulation of light and sound still unachievable real time as such physical accuracy very computationally demanding. Only recently has visual perception been used rendering improve performance by a series novel exploitations; render parts the scene that are not currently being attended viewer much lower quality without difference perceived. This paper...

Recent work on generalized resampled importance sampling (GRIS) enables importance-sampled Monte Carlo integration with random variable weights replacing the usual division by probability density. This very flexible spatiotemporal sample reuse, even if neighboring samples (e.g., light paths) have intractable densities. Unlike typical integration, which according to some PDF, GRIS instead resamples existing samples. But resampling assumes tractable marginal contribution weights, is...

Rendering on conventional computers is capable of generating realistic imagery, but the computational complexity these light transport algorithms a limiting factor image synthesis. Quantum have potential to significantly improve rendering performance through reducing underlying behind transport. This paper investigates hybrid quantum-classical for ray tracing, core component most techniques. Through practical implementation quantum tracing in 3D environment, we show approaches provide...