Image Recognition and Understanding based on the Geometric Information Criterion

1. 从运动图像中进行自我评价我们通过实验证实，利用几何aic可以从原始图像中评估由运动摄像机拍摄的图像进行三维重建的可靠性。我们通过实验证实，在双目立体视觉和两幅图像的三维分析中，几何AIC可以很好地区分物体是平面，物体位于无限远的地方，还是相机只是旋转而不平移。我们通过实验证实，通过使用几何AIC，人类手动输入的规则图形可以自动校正成预期的形状，而无需引入经验阈值。我们还证明了用区间分析可以有效地表示由方程描述的曲线和曲面。从运动图像中检测运动物体我们已经通过实验证实，我们可以通过对运动摄像机拍摄的场景图像序列应用几何AIC来检测场景中运动的物体。旋转估计我们开发了一种从嘈杂的立体图像中优化计算物体三维旋转的技术，并通过实验证实了它的有效性。6. 我们开发了一种技术，通过将移动机器人拍摄的噪声图像与环境的三维模型相匹配，来优化计算移动机器人的当前位置，并通过实验证实了其有效性。

1. Self-evaluation from motion imagesWe have experimentally confirmed that the reliability of 3-D reconstruction from images taken by a moving camera can be evaluated from the original images by using the geometric AIC.2. Detection of degeneracyWe have experimentally confirmed that in binocular stereo vision and 3-D analysis from two images, the geometric AIC can well distinguish whether the object is a planar surface, the object is located infinitely far away, or the camera is simply rotating without translation.3. CAD interfaceWe have experimentally confirmed that regular figures manually input by humans can auto- matically be corrected into intended shapes without introducing empirical thresholds by the use of the geometric AIC.We have also demonstrated that curves and surfaces described by equations can be displayed efficiently by using interval analysis.4. Moving object detection from motion imagesWe have experimentally confirmed that we can detect objects moving in the scene by applying the geometric AIC to a image sequence of the scene taken by a moving camera.5. Rotation estimationWe have developed a technique for optimally computing the 3-D rotation of objects from their noisy stereo images and experimentally confirmed its effectiveness. 6. Robot self-localization We have developed a technique for optimally computing the current position of a mobile robot by matching a noisy image it takes with the 3-D model of the environment and experimentally confirmed its effectiveness.