CISE Research Resources: A Compute-Intensive Sensor-Based Environment for Research in Computer Vision and Artificial Intelligence
CISE 研究资源:用于计算机视觉和人工智能研究的基于计算密集型传感器的环境
基本信息
- 批准号:0130768
- 负责人:
- 金额:$ 14.12万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2001
- 资助国家:美国
- 起止时间:2001-09-15 至 2003-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
EIA-0130768 Sudeep SarkarUniversity of South FloridaCISE Research Resources: A Compute-Intensive Sensor-Based Environment for Research in Computer Vision and Artificial IntelligenceAutomated learning of grouping parameters for perceptual organization of complex images, modeling and reconstruction of elastic objects from image sequences, real-time matching of buyers and sellers for E-commerce, and learning models from extremely large databases, all require large data storage and a computing environment that supports exploring extremely large parameter spaces along with the ability to process huge quantities of data. A multiprocessor computing environment with substantial memory and disk storage is requested for high-performance computing associated with these four research projects in the general areas of computer vision and artificial intelligence. The compute server will increase the present capabilities by an order of magnitude.In addition, image acquisition devices, including high-resolution color cameras, digital video cameras, stereo cameras, and laser range scanners are requested for gathering color, motion, and range data. The ability to acquire fast range images and motion sequences will enable the consideration of the problem of integrating motion and range into the perceptual organization process. Also, the ability to acquire fast and high-resolution range, with registered color, will facilitate development of physics-based non-rigid algorithms and models that incorporate true material properties, which have, heretofore, not been possible.
EIA-0130768 Sudeep SarkarUniversity of South FloridaCISE研究资源:计算机视觉和人工智能研究的基于计算密集型传感器的环境自动学习复杂图像的感知组织的分组参数,从图像序列中建模和重建弹性对象,电子商务买家和卖家的实时匹配,以及从超大型数据库中学习模型,所有这些都需要大数据存储和支持探索极大参数空间的计算环境,沿着具有处理大量数据的能力。在计算机视觉和人工智能的一般领域中,与这四个研究项目相关的高性能计算需要具有大量内存和磁盘存储的多处理器计算环境。计算服务器将使现有的能力提高一个数量级,此外,还需要图像采集设备,包括高分辨率彩色摄像机、数字摄像机、立体摄像机和激光测距扫描仪,以收集颜色、运动和距离数据。 获取快速距离图像和运动序列的能力将使得能够考虑将运动和距离集成到感知组织过程中的问题。此外,获得快速和高分辨率范围的能力,配准颜色,将促进基于物理的非刚性算法和模型的发展,其中包括真实的材料特性,这在此之前是不可能的。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
The HumanID gait challenge problem: Data sets, performance, and analysis
- DOI:10.1109/tpami.2005.39
- 发表时间:2005-02-01
- 期刊:
- 影响因子:23.6
- 作者:Sarkar, S;Phillips, PJ;Bowyer, KW
- 通讯作者:Bowyer, KW
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Sudeep Sarkar其他文献
Mixing Properties of Stable Random Fields Indexed by Amenable and Hyperbolic Groups
由顺从群和双曲群索引的稳定随机场的混合特性
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Mahan Mj;Parthanil Roy;Sudeep Sarkar - 通讯作者:
Sudeep Sarkar
Efficient Generation of Large Amounts of Training Data for Sign Language Recognition: A Semi-automatic Tool
高效生成大量手语识别训练数据:半自动工具
- DOI:
10.1007/11788713_94 - 发表时间:
2006 - 期刊:
- 影响因子:0
- 作者:
Ruiduo Yang;Sudeep Sarkar;B. Loeding;A. Karshmer - 通讯作者:
A. Karshmer
A modeling approach for burn scar assessment using natural features and elastic property
利用自然特征和弹性特性进行烧伤疤痕评估的建模方法
- DOI:
10.1109/tmi.2004.834625 - 发表时间:
2004 - 期刊:
- 影响因子:10.6
- 作者:
Yong Zhang;Dmitry Goldgof;Sudeep Sarkar;L. Tsap - 通讯作者:
L. Tsap
A sensitivity analysis method and its application in physics-based nonrigid motion modeling
灵敏度分析方法及其在物理非刚体运动建模中的应用
- DOI:
10.1016/j.imavis.2005.08.007 - 发表时间:
2007 - 期刊:
- 影响因子:0
- 作者:
Yong Zhang;Dmitry Goldgof;Sudeep Sarkar;L. Tsap - 通讯作者:
L. Tsap
Different atom trapping geometries with time averaged adiabatic potentials
具有时间平均绝热势的不同原子捕获几何结构
- DOI:
10.1140/epjd/s10053-021-00290-6 - 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Sudeep Sarkar;S. P. Ram;V. B. Tiwari;S. Mishra - 通讯作者:
S. Mishra
Sudeep Sarkar的其他文献
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{{ truncateString('Sudeep Sarkar', 18)}}的其他基金
Collaborative Research: RI:Medium:Understanding Events from Streaming Video - Joint Deep and Graph Representations, Commonsense Priors, and Predictive Learning
协作研究:RI:Medium:理解流视频中的事件 - 联合深度和图形表示、常识先验和预测学习
- 批准号:
1956050 - 财政年份:2020
- 资助金额:
$ 14.12万 - 项目类别:
Continuing Grant
I-Corps Sites: Type II - I-Corps Site at University of South Florida Tampa
I-Corps 站点:II 型 - 南佛罗里达大学坦帕分校 I-Corps 站点
- 批准号:
1829217 - 财政年份:2018
- 资助金额:
$ 14.12万 - 项目类别:
Continuing Grant
I-Corps: Semantic Video - from Video to Descriptions
I-Corps:语义视频 - 从视频到描述
- 批准号:
1647887 - 财政年份:2016
- 资助金额:
$ 14.12万 - 项目类别:
Standard Grant
I-Corps Sites: University of South Florida: Catalyzing Research Translation
I-Corps 网站:南佛罗里达大学:促进研究成果转化
- 批准号:
1449137 - 财政年份:2015
- 资助金额:
$ 14.12万 - 项目类别:
Continuing Grant
RI: Small: Collaborative Research: Ontology based Perceptual Organization of Audio-Video Events using Pattern Theory
RI:小型:协作研究:使用模式理论对音频-视频事件进行基于本体的感知组织
- 批准号:
1217676 - 财政年份:2012
- 资助金额:
$ 14.12万 - 项目类别:
Standard Grant
EMT/Nano: Energy Minimization Computing using Field Coupled Nanomagnets--Modeling and Fabrication
EMT/Nano:使用场耦合纳米磁体的能量最小化计算——建模和制造
- 批准号:
0829838 - 财政年份:2008
- 资助金额:
$ 14.12万 - 项目类别:
Standard Grant
ITR: Fundamental Issues in Automated American Sign Language Recognition
ITR:美国手语自动识别的基本问题
- 批准号:
0312993 - 财政年份:2003
- 资助金额:
$ 14.12万 - 项目类别:
Continuing Grant
Enhancing Undergraduate Computer Science Curriculum through Image Computations: Proof-of-Concept
通过图像计算加强本科计算机科学课程:概念验证
- 批准号:
9980832 - 财政年份:2000
- 资助金额:
$ 14.12万 - 项目类别:
Standard Grant
The Role Learning in Perceptual Organization of Complex Images
复杂图像感知组织中的角色学习
- 批准号:
9907141 - 财政年份:1999
- 资助金额:
$ 14.12万 - 项目类别:
Continuing Grant
Major Research Instrumentation: Acquisition of a Cyberware 3D Scanner to Facilitate State of Art Research in Computer Vision and Graphics
主要研究仪器:购买 Cyberware 3D 扫描仪以促进计算机视觉和图形领域的最先进研究
- 批准号:
9724422 - 财政年份:1997
- 资助金额:
$ 14.12万 - 项目类别:
Standard Grant
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合作研究:CISE-MSI:RPEP:CPS:电网边缘下一代分布式能源的弹性网络物理安全框架
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合作研究:CISE-MSI:RPEP:CPS:电网边缘下一代分布式能源的弹性网络物理安全框架
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