Laboratory for Engineering Man/Machine Systems, Division of Engineering, Brown University, Providence, RI 02912.
IEEE Trans Pattern Anal Mach Intell. 1984 Apr;6(4):418-29. doi: 10.1109/tpami.1984.4767547.
The recognition in image data of viewed patches of spheres, cylinders, and planes in the 3-D world is discussed as a first step to complex object recognition or complex object location and orientation estimation. Accordingly, an image is partitioned into small square windows, each of which is a view of a piece of a sphere, or of a cylinder, or of a plane. Windows are processed in parallel for recognition of content. New concepts and techniques include approximations of the image within a window by 2-D quadric polynomials where each approximation is constrained by one of the hypotheses that the 3-D surface shape seen is either planar, cylindrical, or spherical; a recognizer based upon these approximations to determine whether the object patch viewed is a piece of a sphere, or a piece of a cylinder, or a piece of a plane; lowpass filtering of the image by the approximation. The shape recognition is computationally simple, and for large windows is approximately Bayesian minimum-probability-of-error recognition. These classifications are useful for many purposes. One such purpose is to enable a following processor to use an appropriate estimator to estimate shape, and orientation and location parameters for the 3-D surface seen within a window.
将三维世界中观察到的球体、圆柱体和平面的视场片在图像数据中的识别作为复杂目标识别或复杂目标位置和方向估计的第一步来讨论。因此，图像被分割成小的方形窗口，每个窗口都是球体、圆柱体或平面的一部分的视图。窗口并行处理以识别内容。新概念和技术包括用二维二次多项式逼近窗口内的图像，其中每个逼近都受到以下假设之一的约束，即观察到的三维表面形状是平面、圆柱或球形；基于这些逼近的识别器来确定所观察的对象片是球体、圆柱体还是平面的一部分；用逼近进行图像的低通滤波。形状识别计算简单，对于大窗口，它是近似贝叶斯最小错误概率识别。这些分类对于许多目的都很有用。其中一个目的是使后续处理器能够使用适当的估计器来估计窗口内所见三维表面的形状、方向和位置参数。
