Beymer D, Poggio T
Department of Brain and Cognitive Science, Center for Biological and Computational Learning (CBCL) and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge 02142, USA.
Science. 1996 Jun 28;272(5270):1905-9. doi: 10.1126/science.272.5270.1905.
Computer vision researchers are developing new approaches to object recognition and detection that are based almost directly on images and avoid the use of intermediate three-dimensional models. Many of these techniques depend on a representation of images that induce a linear vector space structure and in principle requires dense feature correspondence. This image representation allows the use of learning techniques for the analysis of images (for computer vision) as well as for the synthesis of images (for computer graphics).
计算机视觉研究人员正在开发新的目标识别和检测方法，这些方法几乎直接基于图像，并且避免使用中间三维模型。其中许多技术依赖于一种能诱导线性向量空间结构的图像表示，原则上需要密集的特征对应。这种图像表示允许使用学习技术来分析图像（用于计算机视觉）以及合成图像（用于计算机图形学）。
