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Implementation of Optical Flow Analysis System Equipped with Reliability Evaluation

具有可靠性评估功能的光流分析系统的实现

基本信息

批准号：
07458067
负责人：
KANATANI Kenichi
金额：
$ 3.26万
依托单位：
GUNMA UNIVERSITY
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
1995
资助国家：
日本
起止时间：
1995 至 1996
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-07458067/
关键词：
image processing image understanding computer vision structure from motion optical flow 3-D recovery information criterion renormalization 動画像ロボットビジョン

项目摘要

1.New optical flow detection methodIntroducing a precise mathematical model of image noise, we presented a scheme for computing optical flow and evaluating its reliability in quantitative terms.2.Robust computational scheme for 3-D reconstructionThe 3-D structure is reconstructed if a matrix called the "flow matrix" can be computed by iterations. The convergence of these iterations turned out to be worse for real image data than for simulated date with artificial noise. We presented a new scheme to guarantee the convergence.3.Mathematical theory of geometric inference from noisy dataIt has turned out that the statistical theory that underlines our 3-D analysis of optical flow can be applied to a wide range of general geometric estimation problems involving image and sensor data. We presented a general theory of "optimal fitting", in which a theoretical accuracy bound was derived as a special form of the "Cramer-Rao lower bound".4.Geometric information criterionExtending the AIC used in statistics, we defined the "geometric information criterion (AIC)" as a measure for predicting to what extend we could expect robust 3-D reconstruction from noisy image data. We applied it to a various problems including stereo image analysis, motion image analysis and graphic interface, confirmed the effectiveness of our formalism.

1.新的光流检测方法引入图像噪声的精确数学模型，提出了一种计算光流并定量评估其可靠性的方案。2.3D重建的鲁棒计算方案如果可以通过迭代计算称为“流矩阵”的矩阵，则可以重建3D结构。事实证明，真实图像数据的这些迭代的收敛性比带有人工噪声的模拟数据的收敛性要差。我们提出了一种新的方案来保证收敛性。3.从噪声数据进行几何推断的数学理论事实证明，强调我们的3D光流分析的统计理论可以应用于涉及图像和传感器数据的广泛的一般几何估计问题。我们提出了“最优拟合”的一般理论，其中理论精度界限被推导为“Cramer-Rao下界”的特殊形式。4.几何信息准则扩展了统计学中使用的AIC，我们将“几何信息准则（AIC）”定义为一种度量，用于预测我们可以从噪声图像数据中期望鲁棒3D重建的程度。我们将其应用于立体图像分析、运动图像分析和图形界面等各种问题，证实了我们形式主义的有效性。