The growth in the use of satellite images has generated the need for their fast compression, processing, and distribution. JPEG2000 is a widespread standard for the compression and transmission of such images once the...
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The growth in the use of satellite images has generated the need for their fast compression, processing, and distribution. JPEG2000 is a widespread standard for the compression and transmission of such images once they are in the ground. Despite its advanced features and excellent coding performance, JPEG2000 demands significant computational resources. This paper introduces a wavelet-based codec that uses the JPEG2000 framework, but replaces its most computationally demanding coding stage by a highly parallel engine. When executed in graphicsprocessing Units to code high-resolution satellite images, the proposed codec achieves speed-ups of up to 8× when compared to the fastest implementation of JPEG2000 executed in a multi-core platform.
computer Vision and Machine Learning are the key to develop autonomous robots. While engaged with a IEEE Open Challenge, in which the robots need to recognize a miniature of a cow, we saw a solution in these areas. Th...
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ISBN:
(纸本)9781538609569
computer Vision and Machine Learning are the key to develop autonomous robots. While engaged with a IEEE Open Challenge, in which the robots need to recognize a miniature of a cow, we saw a solution in these areas. The main contribution of this paper is the algorithm implemented to identify and follow a known object, the miniature of a cow. We are constructing an application based on imageprocessing that can detect in images this previously known object. The method yields the limits and the mass center of the entity and appropriates known algorithms, as well as Shi-Tomasi Corner Detector, the clustering K-means and local binary patterns.
We present a novel framework for real-time procedural distribution of vegetation, capable of handling large-scale terrains. Our approach considers several natural aspects that influence the adaptability of each plant ...
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ISBN:
(数字)9781538696057
ISBN:
(纸本)9781538696064
We present a novel framework for real-time procedural distribution of vegetation, capable of handling large-scale terrains. Our approach considers several natural aspects that influence the adaptability of each plant type to topographic and environmental factors displayed across the terrain, as well as interactions between different plant types. The adaptability of each plant type is modeled through a set of consistent parameters that afford full control to the user over the final results of the distribution process. The proposed architecture relies on GPU parallelization and GPU instancing to improve performance. Our framework can be used to generate the vegetation cover of a terrain at runtime or to create an initial distribution that could latter be manually edited, expediting the process of decorating large environments. The results show that our framework can achieve natural looking vegetation distributions, while maintaining the computational costs compatible with realtime applications.
Pathfinding algorithms are at the heart of most games, especially to fulfill increasingly demanding Artificial Intelligence and Level Design tasks. Recent smartphones and tablets are equipped with efficient Multi-Proc...
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ISBN:
(数字)9781538696057
ISBN:
(纸本)9781538696064
Pathfinding algorithms are at the heart of most games, especially to fulfill increasingly demanding Artificial Intelligence and Level Design tasks. Recent smartphones and tablets are equipped with efficient Multi-processing Systemson-Chip (MPSoC) devices, with demanding performance requirements and energy consumption constraints. While not primarily designed for gaming, such mobile machines are quickly climbing to the top of the list of preferred gaming devices, augmented at each new product iteration with stateof-the-art multimedia subsystems and co-processors. Therefore, this work aims at designing and evaluating an efficient A* pathfinding co-processor for reconfigurable gaming devices. The co-processor is designed using Xilinx High-Level Synthesis (HLS) compiler and is implemented in the programming logic of a Xilinx Ultrascale+ Field-Programmable Gate Array (FPGA) embedded with a 64-bit quad-core ARM Cortex-A53 MPSoC, dual-core Cortex-R5 real-time processors, and a Mali400 MP2 graphicsprocessing unit. Extensive performance, circuit-area and energy consumption results shows that the coprocessor running at only 200MHz can efficiently find paths approximately four times faster than one ARM processor running at 1.2GHz for a set of pathfinding benchmarks based on artificial maps and commercial games such as StarCraft and Baldur's Gate, paving the way for novel dedicated gaming co-processors. Moreover, the co-processor only requires about one third of the system's total dynamic power.
NASA Technical Reports Server (Ntrs) 19870019691: Proceedings: computer Science and Data Systems Technical symposium, Volume 1 by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 19870019691: Proceedings: computer Science and Data Systems Technical symposium, Volume 1 by NASA Technical Reports Server (Ntrs); published by
Streaming high quality rendering for virtual reality applications requires minimizing perceived latency. We introduce Shading Atlas Streaming (SAS) [1], a novel object-space rendering framework suitable for streaming ...
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ISBN:
(纸本)9781538675939;9781538675922
Streaming high quality rendering for virtual reality applications requires minimizing perceived latency. We introduce Shading Atlas Streaming (SAS) [1], a novel object-space rendering framework suitable for streaming virtual reality content. SAS decouples server-side shading from client-side rendering, allowing the client to perform framerate upsampling and latency compensation autonomously for short periods of time. The shading information created by the server in object space is temporally coherent and can be efficiently compressed using standard MPEG encoding. Our results show that SAS compares favorably to previous methods for remote image-based rendering in terms of image quality and network bandwidth efficiency. SAS allows highly efficient parallel allocation in a virtualized-texture-like memory hierarchy, solving a common efficiency problem of object-space shading. With SAS, untethered virtual reality headsets can benefit from high quality rendering without paying in increased latency. Visitors will be able to try SAS by roaming the exhibit area wearing a Snapdragon 845 based headset.
Photographers routinely compose multiple manipulated photos of the same scene into a single image, producing a fidelity difficult to achieve using any individual photo. Alternately, 3D artists set up rendering systems...
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Photographers routinely compose multiple manipulated photos of the same scene into a single image, producing a fidelity difficult to achieve using any individual photo. Alternately, 3D artists set up rendering systems to produce layered images to isolate individual aspects of the light transport, which are composed into the final result in post-production. Regrettably, these approaches either take considerable time and effort to capture, or remain limited to synthetic scenes. In this paper, we suggest a method to decompose a single image into multiple layers that approximates effects such as shadow, diffuse illumination, albedo, and specular shading. To this end, we extend the idea of intrinsic images along two axes: first, by complementing shading and reflectance with specularity and occlusion, and second, by introducing directional dependence. We do so by training a convolutional neural network (CNN) with synthetic data. Such decompositions can then be manipulated in any off-the-shelf image manipulation software and composited back. We demonstrate the effectiveness of our decomposition on synthetic (i. e., rendered) and real data (i. e., photographs), and use them for photo manipulations, which are otherwise impossible to perform based on single images. We provide comparisons with state-of-the-art methods and also evaluate the quality of our decompositions via a user study measuring the effectiveness of the resultant photo retouching setup. Supplementary material and code are available for research use at .
The counting of people in a room or a building is a desirable feature in a Smart City environment. There are several hardware systems that simplify this process. However, those systems tend to be very intrusive. This ...
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Distribution effects such as diffuse global illumination, soft shadows and depth of field, are most accurately rendered using Monte Carlo ray or path tracing. However, physically accurate algorithms can take hours to ...
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Distribution effects such as diffuse global illumination, soft shadows and depth of field, are most accurately rendered using Monte Carlo ray or path tracing. However, physically accurate algorithms can take hours to converge to a noise-free image. A recent body of work has begun to bridge this gap, showing that both individual and multiple effects can be achieved accurately and efficiently. These methods use sparse sampling, GPU raytracers, and adaptive filtering for reconstruction. They are based on a Fourier analysis, which models distribution effects as a wedge in the frequency domain. The wedge can be approximated as a single large axis-aligned filter, which is fast but retains a large area outside the wedge, and therefore requires a higher sampling rate;or a tighter sheared filter, which is slow to compute. The state-of-the-art fast sheared filtering method combines low sampling rate and efficient filtering, but has been demonstrated for individual distribution effects only, and is limited by high-dimensional data storage and processing. We present a novel filter for efficient rendering of combined effects, involving soft shadows and depth of field, with global (diffuse indirect) illumination. We approximate the wedge spectrum with multiple axis-aligned filters, marrying the speed of axis-aligned filtering with an even more accurate (compact and tighter) representation than sheared filtering. We demonstrate rendering of single effects at comparable sampling and frame-rates to fast sheared filtering. Our main practical contribution is in rendering multiple distribution effects, which have not even been demonstrated accurately with sheared filtering. For this case, we present an average speedup of 6x compared with previous axis-aligned filtering methods.
NASA Technical Reports Server (Ntrs) 19870019711: Proceedings: computer Science and Data Systems Technical symposium, Volume 2 by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 19870019711: Proceedings: computer Science and Data Systems Technical symposium, Volume 2 by NASA Technical Reports Server (Ntrs); published by
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