The SIFT keys derived from an image are used in a nearest-neighbour approach to indexing to identify candidate object models. Collections of keys that agree on a potentialmodel pose are first identified through a Hough transform
hash table, and then through a least-squares fit to a final estimate of model parameters. When at least 3 keys agree on the model parameters with low residual, there is strong evidence for the presence of the object. Since there may be dozens of SIFT keys in the image of a typical object, it ispossible to have substantial levels of occlusion in the image and yet retain high levels of reliability.
The current object models are represented as 2D locations of SIFT keys that can undergo affine projection. Sufficient variation in feature location is allowed to recognize perspective projection of planar shapes at up to a 60 degree rotation away from the camera or to allow up to a 20 degree rotation of a 3D object.

SIFT键来自于一幅图像，用于近邻法索引，以确定候选对象模型。这些可能的模型构成的键的集合是首次通过霍夫变换和哈希表，然后通过最小乘方拟合的最后估计模型参数。当有3个键低残余地符合模型参数，就是存在对象的有力证据。由于可能有几十个SIFT键存在于典型对象的图像里面，可能会有相当程度的阻塞但仍保留高水平的可靠性。
在当前对象模型代表SIFT键的二维位置，可以进行仿射投影。特征定位的足够变化允许在远离相机高达60度旋转或三维物体多达20度旋转的情况下识别平面形状的透视投影。