视觉的物理不变量

I. Weiss
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引用次数: 2

摘要

与几何不变量不同,这里描述的不变量涉及形成图像的物理过程,包括阴影、红外、雷达、声纳等。这种过程形成的图像除了几何形状外,还取决于许多变量,如照明或其他入射辐射的特性、成像系统等。大多数这些变量都是事先不知道的,所以形状的恢复是困难的。如果我们能找到情况的不变量,即当一些未知变量改变时保持不变的量,这个问题就会大大简化。在本文中,我们应用已知的数学物理方法来求物理成像过程的不变量。这些方法利用了各种对称性,这些对称性可以作为基于模型的识别方法的一部分。作为一个例子,我们使用的形状从阴影问题,但方法有更广泛的适用性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Physics-like invariants for vision
Unlike geometric invariants, the invariants described here concern the physical processes that form images, involving shading, IR, radar, sonar, etc. The image formed by such a process depends on many variables in addition to the geometry, such as the characteristics of the lighting or other incident radiation, the imaging system, etc. Most of these variables are not known in advance, so the recovery of shape is difficult. The problem could be greatly simplified if we could find invariants of the situation, namely quantities that stay unchanged as some of the unknown variables change. In this paper we apply known methods of mathematical physics to finding invariants of physical imaging processes. These methods take advantage of various symmetries, which can be part of a model-based approach to recognition. As an example we use the shape from shading problem, but the methods have a much wider applicability
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