II-New: High-Definition and Immersive Acquisition, Processing, and Display Equipment for Video Processing and Vision Science Research and Education
II-新:用于视频处理和视觉科学研究和教育的高清沉浸式采集、处理和显示设备
基本信息
- 批准号:0854904
- 负责人:
- 金额:$ 20.59万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2009
- 资助国家:美国
- 起止时间:2009-07-15 至 2012-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
New, state-of-the-art video quality assessment (VQA) algorithms will be developed that are explicitly designed for use on High Definition (HD) video streams. These will be designed using perceptual criteria and taking into account such human factors as head and eye position. An open database of raw digital HD videos will be developed, along with multiple distorted versions of each video and human subjective scores on the distorted videos. Since HD videos are often resized for display on smaller screen, scalable VQA and IQA algorithms will also be developed that will for the first time, be able to assess the quality of images or videos, in a perceptually significant way that have been scaled or resized from their original dimensions. The development of successful HD Video Quality Assessment (VQA) algorithms that correlate highly with visual perception will represent a major advance in video engineering. The construction of an HD video quality database will be the first of is kind, and certainly heavily accessed by researchers around the world. Prior work by this group on non-HD VQA has resulted in some of the most-highly cited research in the image processing field in the past 20 years. It is anticipated that publications from this work will likewise be highly influential.The equipment and developed algorithms will also be used as exemplars in the UT-Austin image and video processing educational program. The equipment will be used to generate numerous video processing teaching examples.
将开发新的、最先进的视频质量评估(VQA)算法,这些算法明确设计用于高清(HD)视频流。这些将使用感知标准进行设计,并考虑到头部和眼睛位置等人为因素。将开发一个原始数字高清视频的开放数据库,沿着每个视频的多个失真版本和失真视频上的人类主观评分。由于高清视频经常被调整大小以在更小的屏幕上显示,因此还将开发可扩展的VQA和IQA算法,这将是第一次能够以感知上显著的方式评估图像或视频的质量,这些图像或视频已经从原始尺寸缩放或调整大小。成功的高清视频质量评估(VQA)算法的开发与视觉感知高度相关,将代表视频工程的重大进展。高清视频质量数据库的建设将是第一个,肯定会被世界各地的研究人员大量访问。在过去的20年里,这个小组在非HD VQA方面的工作已经导致了图像处理领域中一些被引用最多的研究。预计这项工作的出版物也将具有很大的影响力。设备和开发的算法也将被用作UT-奥斯汀图像和视频处理教育计划的范例。该设备将用于生成大量的视频处理教学实例。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Alan Bovik其他文献
Alan Bovik的其他文献
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{{ truncateString('Alan Bovik', 18)}}的其他基金
RI: Small: Tasking on Natural Image Statistics: 2D and 3D Object and Category Detection in the Wild
RI:小型:自然图像统计任务:野外 2D 和 3D 对象和类别检测
- 批准号:
1526423 - 财政年份:2015
- 资助金额:
$ 20.59万 - 项目类别:
Continuing Grant
RI: Small: Intelligent Autonomous Video Quality Agents
RI:小型:智能自主视频质量代理
- 批准号:
1116656 - 财政年份:2011
- 资助金额:
$ 20.59万 - 项目类别:
Standard Grant
ITR: Foundations of Visual Search
ITR:视觉搜索的基础
- 批准号:
0427372 - 财政年份:2004
- 资助金额:
$ 20.59万 - 项目类别:
Continuing Grant
Blind Image and Video Quality Assessment Using Natural Scene Statistics
使用自然场景统计进行盲图像和视频质量评估
- 批准号:
0310973 - 财政年份:2003
- 资助金额:
$ 20.59万 - 项目类别:
Continuing Grant
Integrated Sensing: Active Stereoscopic Visual Search Driven by Natural Scene Statistics
集成传感:自然场景统计驱动的主动立体视觉搜索
- 批准号:
0225451 - 财政年份:2002
- 资助金额:
$ 20.59万 - 项目类别:
Continuing Grant
Numerical Instrumentation for Shape and Shape Change Analysis via Three-Dimensional Microscopy
通过三维显微镜进行形状和形状变化分析的数值仪器
- 批准号:
9106624 - 财政年份:1991
- 资助金额:
$ 20.59万 - 项目类别:
Continuing Grant
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