Stable Realization of Virtual Reality by Model Selection

1.3-D重建从图像我们已经提出了一个理论计算的三维结构的场景和对象从图像与最大可能的准确性和评估的可靠性计算的解决方案在定量方面。我们已经证明了我们的理论的有效性，将其应用到3-D重建从两个图像和3-D解释的光流。我们还展示了如何计算的协方差矩阵，表征的准确性，从图像中提取的特征点，并通过实验证实了他们的正相关性与他们的可靠性评估。我们进一步分析了绝对位置和尺度的归一化对描述计算形状可靠性的影响。提出了一种新的曲线曲面显示技术，为图像三维重建的可靠性评价提供了理论基础。2.几何模型选择的虚拟现实实现导出了“几何AIC”和“几何MDL”作为图像噪声数据几何推理的模型选择准则，并给出了信息论解释。我们已经将这些标准应用于图像拼接，并证明即使捕获的图像之间的重叠很小，图像变换也可以稳定地计算。我们还设计了一种用于校准虚拟演播室应用的移动相机的最佳参考图案，并通过模拟和真实的证实。图像实验表明，通过引入几何模型，可以避免相机配置的退化和解的统计波动选择.此外，我们已经证明了通过模拟和真实图像实验，分离独立的对象运动和估计的对象从他们的运动图像的数量的准确性，可以显着提高通过引入几何模型选择。

1.3-D reconstruction from imagesWe have presented a theory for computing the 3-D structure of the scene and objects from images with maximum possible accuracy and evaluating the reliability of the computed solution in quantitative terms. We have demonstrated the effectiveness of our theory by applying it to 3-D reconstruction from two images and 3-D interpretation of optical flow.We have also shown how to compute the covariance matrices that characterize the accuracy of feature points extracted from images and experimentally confirmed their positive correlation with their reliability evaluation. We have further analyzed the effects of normalization of the absolute position and the scale for describing the reliability of the computed shape. A new technique for displaying curves and surfaces are also proposed.We have thus given a theoretical foundation to the reliability evaluation of 3-D reconstruction from images.2.Virtual reality realization by geometric model selectionyWe have derived the "geometric AIC" and the "geometric MDL" as model selection criteria for geometric inference of noisy data extracted from images and given an information-theoretic interpretation. We have applied these criteria to image mosaicing and demonstrated that the image transformation can be stably computed even if the overlaps between captured images are small.We have also designed an optimal reference pattern for calibrating a moving camera for virtual studio applications and confirmed by simulations and real-image experiments that the degeneracy of camera configuration and statistical fluctuations of the solution can be avoided by incorporating geometric model selection. Furthermore, we have demonstrated by simulations and real-image experiments that the accuracy of separating independent object motions and estimating the number of objects from their motion images can be dramatically improved by introducing geometric model selection.