CIF: Small: Geometric, Variational Algorithms for Radiometric-Based Shape Reconstruction

CIF:小:基于辐射的形状重建的几何变分算法

基本信息

  • 批准号:
    1526848
  • 负责人:
  • 金额:
    $ 50万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-08-01 至 2019-07-31
  • 项目状态:
    已结题

项目摘要

The investigator will develop a new class of variational geometric inverse algorithms for reconstructing dense 3D shape of objects from measurements of a scene representing an arbitrary combination of vantage points and/or resolution by employing a common mathematical framework based on generative radiometric models. Reconstruction of shape from raw sensor data is a necessary step for graphical 3D rendering and analysis in scenarios where CAD models are unavailable or impossible. Two examples to be initially explored include unfocussed camera images from different viewpoints and/or focal lengths using thin-lens modelling, and radar signals reflected from nearby objects with different antenna locations and/or wavelengths.The framework will be general enough to apply to several related sensor modalities beyond those initially investigated, ranging from infrared, acoustics, and SAR. Furthermore, having a unified model affords the freedom to generate flexible data capture and fusion schemes where not one, but multiple sets of measurements are captured under different viewpoint and sensor setting characteristics, and use the entire set of collected data to infer an estimate of reflectance and geometry that is of superior quality relative to what may be obtained in scenarios where "isolating a single cue" is not possible. For instance, with cameras, it may be impossible to fix the viewpoint while capturing images of different focus (isolating focus), or to capture perfectly sharp images because of the finite aperture of the lens (isolating viewpoint). Removing this constraint can enable applications to endoscopy, inspection of pipes and crevices, dental impressions, as well as environmental monitoring.
研究人员将开发一类新的变分几何逆算法,通过采用基于生成辐射模型的通用数学框架,根据代表有利点和/或分辨率的任意组合的场景测量来重建物体的密集 3D 形状。在 CAD 模型不可用或不可能的情况下,从原始传感器数据重建形状是图形 3D 渲染和分析的必要步骤。最初探索的两个例子包括使用薄透镜建模从不同视点和/或焦距拍摄的未聚焦相机图像,以及从具有不同天线位置和/或波长的附近物体反射的雷达信号。该框架足够通用,足以适用于多种应用相关传感器模式超出了最初研究的范围,包括红外、声学和合成孔径雷达。此外,拥有统一的模型可以自由地生成灵活的数据捕获和融合方案,其中不是在不同的视点和传感器设置特性下捕获一组测量值,而是捕获多组测量值,并使用整组收集的数据来推断反射率的估计相对于在不可能“隔离单个提示”的情况下可能获得的几何形状,其质量更高。例如,对于相机,可能无法在捕捉不同焦点的图像时固定视点(隔离焦点),或者由于镜头的有限光圈(隔离视点)而无法捕捉完美清晰的图像。消除这一限制可以应用于内窥镜检查、管道和缝隙检查、牙科印模以及环境监测。

项目成果

期刊论文数量(0)
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科研奖励数量(0)
会议论文数量(0)
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Anthony Yezzi其他文献

Event-Based Eye Tracking. AIS 2024 Challenge Survey
基于事件的眼动追踪。
  • DOI:
    10.48550/arxiv.2404.11770
  • 发表时间:
    2024-04-17
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zuowen Wang;Chang Gao;Zongwei Wu;Marcos V. Conde;R. Timofte;Shih;Qinyu Chen;Zheng;Wei Zhai;Han Han;Bohao Liao;Yuliang Wu;Zengyu Wan;Zhong Wang;Yang Cao;Ganchao Tan;Jinze Chen;Yan Ru Pei;Sasskia Bruers;S'ebastien Crouzet;Douglas McLell;Oliver Coenen;Baoheng Zhang;Yizhao Gao;Jingyuan Li;Hayden Kwok;Philippe Bich;Chiara Boretti;Luciano Prono;Mircea Licua;David Dinucu;Cuatualin Griu;Xiaopeng Lin;Hong Ren;Bo;Xinan Zhang;Valentin Vial;Anthony Yezzi;James Tsai
  • 通讯作者:
    James Tsai
A variational framework for joint segmentation and registration
联合分割和配准的变分框架
Phase transitions, curve evolution, and the control of semiconductor manufacturing processes
相变、曲线演化和半导体制造工艺的控制
Performance of detection statistics under collusion attacks on independent multimedia fingerprints
独立多媒体指纹共谋攻击下的检测统计性能
  • DOI:
    10.1109/icme.2003.1220890
  • 发表时间:
    2003-07-06
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Thinh Nguyen;Puneet Mehra;A. Zakhor;Susie Wee;John G. Apostolopoulos;Wai;S. Roy;Jacob Chakareski;Eric Setton;Yi Liang;Bernd Girod;M. Fumagalli;Cefriel;Italy;P. Sagetong;Antonio Ortega;Amy Reibman;V. Vaishampayan;Rémi Ronfard;Tien Tran Thuong;France Inria;Xiaofei He;Adam Berenzweig;Daniel P W Ellis;Tong Zhang;M. Boutell;Yeow Kee Tan;N. Sherkat;Tony Allen;Y. Sawahata;Kiyoharu Aizawa;Timothy T H Chen;Sidney Fels;Sarah Saehee;Min;Xin Fan;China;Xing Xie;Wei;Hong;Björn Schuller;M. Zobl;G. Rigoll;Manfred Lang;Hsuan;Shrikanth S Narayanan;C.;Rongshan Yu;Xiao Lin;S. Rahardja;Simon Lucey;Tsuhan Chen;M. Reyes;Chih;Sau;Yongmin Li;Li;Geoff Morrison;Charles Nightingale;J. Morphett;Jun;John Zhang;Jagath Chen;Samarab;u;u;S. H. Srinivasan;M. Kankanhalli;Wei;Hasan Ates;Andy Chang;Oscar C. Au;Ming Yeung;Hong Kong;Gulcin Caner;Yu Hen Hu;Rajas A. Sambhare;N. Bellas;M. Dwyer;Tay;Chin;Tsung;Yu;Chien;Chen;Hung;C. Jen;Satoshi Nishiguchi;Kazuhide Higashi;Y. Kameda;Tsung;Wen;Chun;Hung;Tu;Yu;Ya;Liang;Jongmyon Kim;Scott Wills;Michelle Yan;J. Shaw;Shinsuke Kobayashi;Kentaro Mita;Yoshinori Takeuchi;Ioannis Andreou;N. Sgouros;Michael Lee;Surya Nepal;Uma Srinivasan;Csiro;Australia;Gees Stein;J. Rittscher;A. Hoogs;H. Nagano;K. Kashino;Hiroshi Murase;Ahmet Ekin;Amit Chakraborty;P. Liu;L. Hsu;Lijun Yin;Sergey Royt;Francis Quek;Yingen Xiong;Haitao Zheng;J. Taal;I. Haratcherev;K. Langendoen;T. Stockhammer;Jie Chen;S. Hsia;Trista Pei;Hong Zhao;Min Wu;Z. J. Wang;K. Liu;A. Giannoula;A. Tefas;N. Nikolaidis;I. Pitas;M. Fu;N. Cvejic;D. Tujkovic;T. Seppänen;Jonathan Foote;John Adcock;Andreas Girgensohn;S. Mallick;Mohan Trivedi;Inmaculada Rodríguez;Manuel Peinado;Cha Zhang;Yuzhong Shen;K. Barner;Yong;Jang;Dae;Jong;Wende Zhang;Thang Viet Nguyen;Ch;ra Patra;ra;Ee;Wei Wang;Aidong Zhang;S. Palanivel;B. Venkatesh;B. Yegnanarayana;Dong;Michael R. Lyu;D. Trossen;Hemant Chaskar;Shengjie Zhao;Zixiang Xiong;A. Bhatkar;R. Ch;ramouli;ramouli;Wen Xu;S. Hemami;Wanghong Yuan;Klara Nahrstedt;Jiancong Chen;S.;Jieh Hsiang;Wen;Bee;Hsieh;J. Assfalg;A. Bimbo;P. Pala;Xiangdong Zhou;Qi Zhang;Jun Gao;G. Tzanetakis;P. Steenkiste;Lei Zhang;Yu;Xin Huang;Shu;Minghong Pi;Mrinal M;al;al;Anup Basu;G. Iyengar;H. Nock;C. Neti;Min Xu;Ling;Chang Xu;Qi Tian;Ching;Shao;Yi;Yu;A. Pinho;Antonio Neves;Nejat Kamaci;Y. Altunbasak;Xiaodong Gu;Microsoft Research;Asia;Yung;Ming;Yu;Martin Boliek;Kok Wu;Shou;Liang Zhang;Yuhua Ding;G. Vachtsevanos;Anthony Yezzi;Wayne Daley;Bonnie Heck;Chuo;P. Ramanathan;Xiaoqing Zhu;Christian Ritz;Ian Burnett;J. Lukasiak;H. Zarrinkoub;Om Deshmukh;Carol Y. Espy;K. S. Rao;Arun Kumar;Xiaodong He;Dong Wang;J. Pinquier;Jean;R. André;France Top;Mohammed Chalil;Sreekumar K P;Manoj Sankar;A. Raouzaiou;K. Karpouzis;S. Kollias;Ghassan Al;Magy Seif El;I. Horswill;Son Tran;Raghavendra Singh;Ravi Kothari;M. Naphade;States Apostol;Paul Natsev;Belle L. Tseng;John R Smith;Shinsuke Nakajima;Apostol;W. Kumwilaisak;Research Asia;Bo Shen;Sheau;Chun;Rajeev Kumar;Nam Pham;Ngoc;K. Leuven;Belgium;G. Lafruit;J. Mignolet;S. Vernalde;G. Deconinck;Rudy Lauwereins;Belgium Top;Pun;Tien;Amit Kale;Roy Chowdhury;Sarah John
  • 通讯作者:
    Sarah John
Medical image segmentation via coupled curve evolution equations with global constraints
通过具有全局约束的耦合曲线演化方程进行医学图像分割

Anthony Yezzi的其他文献

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{{ truncateString('Anthony Yezzi', 18)}}的其他基金

Shape Based Tomographic Inversion for Maximal Geometric Resolution
基于形状的层析成像反演以获得最大几何分辨率
  • 批准号:
    1347191
  • 财政年份:
    2013
  • 资助金额:
    $ 50万
  • 项目类别:
    Standard Grant
I-Corps: A Clinician's Segmentation/Registration Tool
I-Corps:临床医生的细分/注册工具
  • 批准号:
    1265342
  • 财政年份:
    2012
  • 资助金额:
    $ 50万
  • 项目类别:
    Standard Grant
New Directions in Active Contours by Reformulating Geometric Gradients
通过重新制定几何梯度来实现主动轮廓的新方向
  • 批准号:
    0728911
  • 财政年份:
    2007
  • 资助金额:
    $ 50万
  • 项目类别:
    Standard Grant
CAREER: Unifying Segmentation and Other Image Processing Problems via Variational PDE's
职业:通过变分偏微分方程统一分割和其他图像处理问题
  • 批准号:
    0133736
  • 财政年份:
    2002
  • 资助金额:
    $ 50万
  • 项目类别:
    Continuing Grant

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    59805022
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    1998
  • 资助金额:
    12.0 万元
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CT图象处理及几何重建中的小波与CAGD方法
  • 批准号:
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