607 research outputs found

    Adaptive foveated single-pixel imaging with dynamic super-sampling

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    As an alternative to conventional multi-pixel cameras, single-pixel cameras enable images to be recorded using a single detector that measures the correlations between the scene and a set of patterns. However, to fully sample a scene in this way requires at least the same number of correlation measurements as there are pixels in the reconstructed image. Therefore single-pixel imaging systems typically exhibit low frame-rates. To mitigate this, a range of compressive sensing techniques have been developed which rely on a priori knowledge of the scene to reconstruct images from an under-sampled set of measurements. In this work we take a different approach and adopt a strategy inspired by the foveated vision systems found in the animal kingdom - a framework that exploits the spatio-temporal redundancy present in many dynamic scenes. In our single-pixel imaging system a high-resolution foveal region follows motion within the scene, but unlike a simple zoom, every frame delivers new spatial information from across the entire field-of-view. Using this approach we demonstrate a four-fold reduction in the time taken to record the detail of rapidly evolving features, whilst simultaneously accumulating detail of more slowly evolving regions over several consecutive frames. This tiered super-sampling technique enables the reconstruction of video streams in which both the resolution and the effective exposure-time spatially vary and adapt dynamically in response to the evolution of the scene. The methods described here can complement existing compressive sensing approaches and may be applied to enhance a variety of computational imagers that rely on sequential correlation measurements.Comment: 13 pages, 5 figure

    Evaluation of optimisation techniques for multiscopic rendering

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    A thesis submitted to the University of Bedfordshire in fulfilment of the requirements for the degree of Master of Science by ResearchThis project evaluates different performance optimisation techniques applied to stereoscopic and multiscopic rendering for interactive applications. The artefact features a robust plug-in package for the Unity game engine. The thesis provides background information for the performance optimisations, outlines all the findings, evaluates the optimisations and provides suggestions for future work. Scrum development methodology is used to develop the artefact and quantitative research methodology is used to evaluate the findings by measuring performance. This project concludes that the use of each performance optimisation has specific use case scenarios in which performance benefits. Foveated rendering provides greatest performance increase for both stereoscopic and multiscopic rendering but is also more computationally intensive as it requires an eye tracking solution. Dynamic resolution is very beneficial when overall frame rate smoothness is needed and frame drops are present. Depth optimisation is beneficial for vast open environments but can lead to decreased performance if used inappropriately

    Foveated Video Streaming for Cloud Gaming

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    Good user experience with interactive cloud-based multimedia applications, such as cloud gaming and cloud-based VR, requires low end-to-end latency and large amounts of downstream network bandwidth at the same time. In this paper, we present a foveated video streaming system for cloud gaming. The system adapts video stream quality by adjusting the encoding parameters on the fly to match the player's gaze position. We conduct measurements with a prototype that we developed for a cloud gaming system in conjunction with eye tracker hardware. Evaluation results suggest that such foveated streaming can reduce bandwidth requirements by even more than 50% depending on parametrization of the foveated video coding and that it is feasible from the latency perspective.Comment: Submitted to: IEEE 19th International Workshop on Multimedia Signal Processin

    Real-Time Restoration of Images Degraded by Uniform Motion Blur in Foveal Active Vision Systems

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    Foveated, log-polar, or space-variant image architectures provide a high resolution and wide field workspace, while providing a small pixel computation load. These characteristics are ideal for mobile robotic and active vision applications. Recently we have described a generalization of the Fourier Transform (the fast exponential chirp transform) which allows frame-rate computation of full-field 2D frequency transforms on a log-polar image format. In the present work, we use Wiener filtering, performed using the Exponential Chirp Transform, on log-polar (fovcated) image formats to de-blur images which have been degraded by uniform camera motion.Defense Advanced Research Projects Agency and Office of Naval Research (N00014-96-C-0178); Office of Naval Research Multidisciplinary University Research Initiative (N00014-95-1-0409

    Space-variant picture coding

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    PhDSpace-variant picture coding techniques exploit the strong spatial non-uniformity of the human visual system in order to increase coding efficiency in terms of perceived quality per bit. This thesis extends space-variant coding research in two directions. The first of these directions is in foveated coding. Past foveated coding research has been dominated by the single-viewer, gaze-contingent scenario. However, for research into the multi-viewer and probability-based scenarios, this thesis presents a missing piece: an algorithm for computing an additive multi-viewer sensitivity function based on an established eye resolution model, and, from this, a blur map that is optimal in the sense of discarding frequencies in least-noticeable- rst order. Furthermore, for the application of a blur map, a novel algorithm is presented for the efficient computation of high-accuracy smoothly space-variant Gaussian blurring, using a specialised filter bank which approximates perfect space-variant Gaussian blurring to arbitrarily high accuracy and at greatly reduced cost compared to the brute force approach of employing a separate low-pass filter at each image location. The second direction is that of artifi cially increasing the depth-of- field of an image, an idea borrowed from photography with the advantage of allowing an image to be reduced in bitrate while retaining or increasing overall aesthetic quality. Two synthetic depth of field algorithms are presented herein, with the desirable properties of aiming to mimic occlusion eff ects as occur in natural blurring, and of handling any number of blurring and occlusion levels with the same level of computational complexity. The merits of this coding approach have been investigated by subjective experiments to compare it with single-viewer foveated image coding. The results found the depth-based preblurring to generally be significantly preferable to the same level of foveation blurring

    Object Detection Through Exploration With A Foveated Visual Field

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    We present a foveated object detector (FOD) as a biologically-inspired alternative to the sliding window (SW) approach which is the dominant method of search in computer vision object detection. Similar to the human visual system, the FOD has higher resolution at the fovea and lower resolution at the visual periphery. Consequently, more computational resources are allocated at the fovea and relatively fewer at the periphery. The FOD processes the entire scene, uses retino-specific object detection classifiers to guide eye movements, aligns its fovea with regions of interest in the input image and integrates observations across multiple fixations. Our approach combines modern object detectors from computer vision with a recent model of peripheral pooling regions found at the V1 layer of the human visual system. We assessed various eye movement strategies on the PASCAL VOC 2007 dataset and show that the FOD performs on par with the SW detector while bringing significant computational cost savings.Comment: An extended version of this manuscript was published in PLOS Computational Biology (October 2017) at https://doi.org/10.1371/journal.pcbi.100574
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