Thomas Bashford-Rogers

Dynamic range compression by differential zone mapping based on psychophysical experiments

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

Complete Motion Control of a Serious Game against Obesity in Children

Childhood obesity is a major problem in most developed countries, with significant negative impacts on childrens health. A suggested method for reducing obesity, especially for children, are serious games. These could promote healthy eating and increased physical activity. Ideally, they should also increase energy expenditure during play, and not be a sedentary experience. In the preliminary work described here, we produced a demonstration serious game designed to combat childhood obesity. All user interaction for the game was supplied via movement using re-appropriated Wii input devices to maximize physical activity whilst playing. We describe the problems of implementing such an interface, in particular that of overlearning.

Objective and subjective evaluation of High Dynamic Range video compression

A number of High Dynamic Range (HDR) video compression algorithms proposed to date have either been developed in isolation or only-partially compared with each other. Previous evaluations were conducted using quality assessment error metrics, which for the most part were developed for qualitative assessment of Low Dynamic Range (LDR) videos. This paper presents a comprehensive objective and subjective evaluation conducted with six published HDR video compression algorithms. The objective evaluation was undertaken on a large set of 39 HDR video sequences using seven numerical error metrics namely: PSNR, logPSNR, puPSNR, puSSIM, Weber MSE, HDR-VDP and HDR-VQM. The subjective evaluation involved six short-listed sequences and two ranking-based subjective experiments with hidden reference at two different output bitrates with 32 participants each, who were tasked to rank distorted HDR video footage compared to an uncompressed version of the same footage. Results suggest a strong correlation between the objective and subjective evaluation. Also, non-backward compatible compression algorithms appear to perform better at lower output bit rates than backward compatible algorithms across the settings used in this evaluation.

Optimal exposure compression for high dynamic range content

High dynamic range (HDR) imaging has become one of the foremost imaging methods capable of capturing and displaying the full range of lighting perceived by the human visual system in the real world. A number of HDR compression methods for both images and video have been developed to handle HDR data, but none of them has yet been adopted as the method of choice. In particular, the backwards-compatible methods that always maintain a stream/image that allow part of the content to be viewed on conventional displays make use of tone mapping operators which were developed to view HDR images on traditional displays. There are a large number of tone mappers, none of which is considered the best as the images produced could be deemed subjective. This work presents an alternative to tone mapping-based HDR content compression by identifying a single exposure that can reproduce the most information from the original HDR image. This single exposure can be adapted to fit within the bit depth of any traditional encoder. Any additional information that may be lost is stored as a residual. Results demonstrate quality is maintained as well, and better, than other traditional methods. Furthermore, the presented method is backwards-compatible, straightforward to implement, fast and does not require choosing tone mappers or settings.

Enabling stereoscopic high dynamic range video

Stereoscopic and high dynamic range (HDR) imaging are two methods that enhance video content by respectively improving depth perception and light representation. A large body of research has looked into each of these technologies independently, but very little work has attempted to combine them due to limitations in capture and display; HDR video capture (for a wide range of exposure values over 20 f-stops) is not yet commercially available and few prototype HDR video cameras exist. In this work we propose techniques which facilitate stereoscopic high dynamic range (SHDR) video capture by using an HDR and LDR camera pair. Three methods are proposed: one based on generating the missing HDR frame by warping the existing one using a disparity map; increasing the range of LDR video using a novel expansion operator; and a hybrid of the two where expansion is used for pixels within the LDR range and warping for the rest. Generated videos were compared to the ground truth SHDR video captured using two HDR video cameras. Results show little overall error and demonstrate that the hybrid method produces the least error of the presented methods.

Generating stereoscopic HDR images using HDR-LDR image pairs

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 of research has looked into each of these imaging technologies independently, very little work has attempted to combine them. This is mostly due to the current limitations in capture and display. In this article, we mitigate problems of capturing Stereoscopic HDR (SHDR) that would potentially require two HDR cameras, by capturing an HDR and LDR pair and using it to generate 3D stereoscopic HDR content. We ran a detailed user study to compare four different methods of generating SHDR content. The methods investigated were the following: two based on expanding the luminance of the LDR image, and two utilizing stereo correspondence methods, which were adapted for our purposes. Results demonstrate that one of the stereo correspondence methods may be considered perceptually indistinguishable from the ground truth (image pair captured using two HDR cameras), while the other methods are all significantly distinct from the ground truth.

The virtual reconstruction and daylight illumination of the Panagia Angeloktisti

High-fidelity virtual reconstructions can be used as accurate 3D representations of historical environments. After modelling the site to high precision, physically-based and historically correct light models must be implemented to complete an authentic visualisation. Sunlight has a major visual impact on a site; from directly lit areas to sections in deep shadow. The scene illumination also changes substantially at different times of the day. In this paper we present a virtual reconstruction of the Panagia Angeloktisti; a Byzantine church on Cyprus. We investigate lighting simulations of the church at different times of the day, making use of Image-Based Lighting, using High Dynamic Range Environment Maps of photographs and interpolated spectrophotometer data collected on site. Furthermore, the paper also explores the benefits and disadvantages of employing unbiased rendering methods such as Path Tracing and Metropolis Light Transport for cultural heritage applications.

Importance Driven Environment Map Sampling

In this paper we present an efficient method for supporting image based lighting (IBL) for bidirectional methods. This improves both sampling of the environment, and the detection and sampling of important regions of the scene, such as windows and doors. These parts of the scene often have a small area proportional to that of the entire scene, so paths which pass through them are generated with a low probability. The method proposed in this paper improves sampling efficiency, by taking into account view importance, and modifies the lighting distribution to use light transport information from the camera. This method automatically constructs a sampling distribution in locations which are relevant to the camera position, thereby improving sampling of light paths. This approach can be applied to several bidirectional rendering methods, and results are shown for bidirectional path tracing, metropolis light transport and progressive photon mapping. When compared to other methods, efficiency results demonstrate speed ups of orders of magnitude.

A Significance Cache for Accelerating Global Illumination

Rendering using physically based methods requires substantial computational resources. Most methods that are physically based use straightforward techniques that 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. Most current approaches for physically based rendering based on Monte Carlo methods sample the BRDF and cosine term, but are unable to sample the indirect illumination as this is the term that is being computed. Knowledge of the incoming illumination can be especially useful in the case of hard to find light paths, such as caustics or scenes which rely primarily on indirect illumination. To facilitate the determination of such paths, we propose a caching scheme which stores important directions, and is analytically sampled to calculate important paths. Results show an improvement over BRDF sampling and similar illumination importance sampling.

A physically-based client-server rendering solution for mobile devices

Mobile devices, also known as small-form-factor (SFF) devices such as mobile phones, PDAs and ultra mobile PCs have continued to grow in popularity. Improvements in SFF hardware has enabled a range of suitable applications such as gaming, interactive visualisation and mobile mapping. Although high-fidelity graphic systems typically have significant computational requirements, the time taken may be largely resolution dependent. The limited resolution of SFFs indicates such platforms are prime candidates for running high-fidelity graphics. Due to the limited hardware available on mobile devices, it is not currently possible to produce high-fidelity graphics in reasonable time. However, most SFFs have some degree of network capability. Using a remote server in conjunction with a mobile device to render high-fidelity graphics on demand allows us to substantially reduce the total rendering time. This paper introduces a client-server framework for minimising rendering times using a cost function to predict optimal distribution of rendering.