RUI: Computer Vision and Image Understanding (Computer and Information Science)

本研究项目涉及四个基本问题， 计算机视觉和图像理解。 (1)从图像中恢复三维形状 强度 使用光度立体和其他结构 照明模型，一个系统的方法来恢复完整的 局部表面几何形状和曲面片的重建 将开发图像信息。 (2)岩石变形和运动参数的恢复 必然是刚性物体。 长期以来， 在计算机视觉和机器人技术中的假设。 对于运动分析， 这一假设将被放宽。 许多已知的结果将是 被包容了 虽然一般没有唯一性结果， 对于某些特殊情况，将导出封闭形式的解。 (3)三维空间的对应问题 几何特征 使用光度立体和其他 结构化照明模型，局部和全局三维 将从对象中提取几何特征以建立 图像序列的对应关系。 (4)使用范围数据的对象识别。 参数曲面 将使用范围数据构建补丁。 高效 将开发算法来计算 这样的表面，使他们可以用来 重建/识别/学习世界空间中的对象。

This research project is concerned with four basic problems in computer vision and image understanding. (1) Recovery of three-dimensional shape from image intensities. Using photometric stereo and other structural lighting models, a systematic approach to recovery of complete local surface geometry and reconstruction of surface patches from image information will be developed. (2) Recovery of deformation and motion parametersof not necessarily rigid objects. Rigidity has long been a key assumption in computer vision aNd robotics. For motion analysis, this assumption will be relaxed. Many known results will be subsumed. Although there is no uniqueness result in general, closed form solutions will be derived for certain special cases. (3) The correspondence problem using three-dimensional geometric features. Using photometric stereo and other structured lighting models, local and global three-dimensional geometric features will be extracted from objects to establish correspondence of image sequences. (4) Object recognition using range data. Parametric surface patches will be constructed using range data. Efficient algorithms will be developed to calculate geometric features of such surfaces so that they may be used to reconstruct/recognize/learn objects in world space.