本文详细介绍了计算机视觉中的Bag of Visual Words（BOW）模型，分为三个步骤：特征检测，提取图像关键点；特征描述，使用如SIFT等描述符将关键点转化为数值向量；代码本生成，通过k-means聚类创建代码本，并用码字来表示图像。
第一步：Feature detection
In computer vision and image processing the concept of feature detection refers to methods that aim at computing abstractions of image information and making local decisions at every image point whether there is an image feature of a given type at that point or not. The resulting features will be subsets of the image domain, often in the form of isolated points, continuous curves or connected regions.
Common feature detectors and their classification:
| Feature detector | Edge |
|---|
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