Bayesian statistical fusion models based on constraints and multiple criteria in image processing and computer vision
图像处理和计算机视觉中基于约束和多标准的贝叶斯统计融合模型
基本信息
- 批准号:238737-2011
- 负责人:
- 金额:$ 1.75万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2014
- 资助国家:加拿大
- 起止时间:2014-01-01 至 2015-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
My research program investigates the use of new unsupervised probabilistic or energy-based fusion models for understanding, analyzing, and manipulating still, moving and multidimensional or multi-modal images. More precisely, this research program will attempt to propose new statistical models to integrate multiple (low or higher level) and complementary image cues (e.g., color, texture, edges, corner and interest point detection, symmetry detection, Gestalt laws of perceptual organization, etc.) and/or to exploit one or several low-level applications (segmentation, edge map, restored image, etc.) for the reliable estimation of a final high-level computer vision task (e.g., motion detection/segmentation, occlusion map, complex shape localization, 3D reconstruction, etc.). These problems have a wide range of applications in several fields, including multi-modal medical image applications, geoscience and hyperspectral imagery and more generally in all multi-camera or multi-modal recognition and reconstruction systems of the next generation.
我的研究计划研究使用新的无监督概率或基于能量的融合模型来理解、分析和处理静止、运动和多维或多模式图像。更准确地说,这项研究计划将尝试提出新的统计模型,以整合多个(低或高级别)和互补的图像线索(例如,颜色、纹理、边缘、角点和兴趣点检测、对称性检测、知觉组织的格式塔定律等)。和/或利用一个或多个低级应用(分割、边缘图、恢复图像等)。用于最终高级计算机视觉任务(例如,运动检测/分割、遮挡图、复杂形状定位、3D重建等)的可靠估计。这些问题在多个领域有着广泛的应用,包括多模式医学图像应用、地球科学和高光谱图像,更广泛地说,在所有的下一代多摄像机或多模式识别和重建系统中。
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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Mignotte, Max其他文献
Localization of shapes using statistical models and stochastic optimization
- DOI:
10.1109/tpami.2007.1157 - 发表时间:
2007-09-01 - 期刊:
- 影响因子:23.6
- 作者:
Destrempes, Francois;Mignotte, Max;Angers, Jean-Francois - 通讯作者:
Angers, Jean-Francois
A Novel Fusion Approach Based on the Global Consistency Criterion to Fusing Multiple Segmentations
- DOI:
10.1109/tsmc.2016.2531645 - 发表时间:
2017-09-01 - 期刊:
- 影响因子:8.7
- 作者:
Khelifi, Lazhar;Mignotte, Max - 通讯作者:
Mignotte, Max
A biologically inspired framework for contour detection
- DOI:
10.1007/s10044-015-0494-y - 发表时间:
2017-05-01 - 期刊:
- 影响因子:3.9
- 作者:
Mignotte, Max - 通讯作者:
Mignotte, Max
A non-local regularization strategy for image deconvolution
- DOI:
10.1016/j.patrec.2008.08.004 - 发表时间:
2008-12-01 - 期刊:
- 影响因子:5.1
- 作者:
Mignotte, Max - 通讯作者:
Mignotte, Max
Segmentation by fusion of histogram-based K-means clusters in different color spaces
- DOI:
10.1109/tip.2008.920761 - 发表时间:
2008-05-01 - 期刊:
- 影响因子:10.6
- 作者:
Mignotte, Max - 通讯作者:
Mignotte, Max
Mignotte, Max的其他文献
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{{ truncateString('Mignotte, Max', 18)}}的其他基金
New unsupervised Bayesian and energy-based models dedicated to image processing and computer vision applications
新的无监督贝叶斯和基于能量的模型致力于图像处理和计算机视觉应用
- 批准号:
RGPIN-2022-03654 - 财政年份:2022
- 资助金额:
$ 1.75万 - 项目类别:
Discovery Grants Program - Individual
Bayesian fusion models based on multi-level constraints and multiple criteria in image processing and computer vision
图像处理和计算机视觉中基于多级约束和多准则的贝叶斯融合模型
- 批准号:
RGPIN-2016-04578 - 财政年份:2020
- 资助金额:
$ 1.75万 - 项目类别:
Discovery Grants Program - Individual
Bayesian fusion models based on multi-level constraints and multiple criteria in image processing and computer vision
图像处理和计算机视觉中基于多级约束和多准则的贝叶斯融合模型
- 批准号:
RGPIN-2016-04578 - 财政年份:2019
- 资助金额:
$ 1.75万 - 项目类别:
Discovery Grants Program - Individual
Bayesian fusion models based on multi-level constraints and multiple criteria in image processing and computer vision
图像处理和计算机视觉中基于多级约束和多准则的贝叶斯融合模型
- 批准号:
RGPIN-2016-04578 - 财政年份:2018
- 资助金额:
$ 1.75万 - 项目类别:
Discovery Grants Program - Individual
Bayesian fusion models based on multi-level constraints and multiple criteria in image processing and computer vision
图像处理和计算机视觉中基于多级约束和多准则的贝叶斯融合模型
- 批准号:
RGPIN-2016-04578 - 财政年份:2017
- 资助金额:
$ 1.75万 - 项目类别:
Discovery Grants Program - Individual
Bayesian fusion models based on multi-level constraints and multiple criteria in image processing and computer vision
图像处理和计算机视觉中基于多级约束和多准则的贝叶斯融合模型
- 批准号:
RGPIN-2016-04578 - 财政年份:2016
- 资助金额:
$ 1.75万 - 项目类别:
Discovery Grants Program - Individual
Bayesian statistical fusion models based on constraints and multiple criteria in image processing and computer vision
图像处理和计算机视觉中基于约束和多标准的贝叶斯统计融合模型
- 批准号:
238737-2011 - 财政年份:2015
- 资助金额:
$ 1.75万 - 项目类别:
Discovery Grants Program - Individual
Bayesian statistical fusion models based on constraints and multiple criteria in image processing and computer vision
图像处理和计算机视觉中基于约束和多标准的贝叶斯统计融合模型
- 批准号:
238737-2011 - 财政年份:2013
- 资助金额:
$ 1.75万 - 项目类别:
Discovery Grants Program - Individual
Bayesian statistical fusion models based on constraints and multiple criteria in image processing and computer vision
图像处理和计算机视觉中基于约束和多标准的贝叶斯统计融合模型
- 批准号:
238737-2011 - 财政年份:2012
- 资助金额:
$ 1.75万 - 项目类别:
Discovery Grants Program - Individual
Bayesian statistical fusion models based on constraints and multiple criteria in image processing and computer vision
图像处理和计算机视觉中基于约束和多标准的贝叶斯统计融合模型
- 批准号:
238737-2011 - 财政年份:2011
- 资助金额:
$ 1.75万 - 项目类别:
Discovery Grants Program - Individual
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