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I am studying something about some possibilities of OpenCV object detection and this is confusing to me. I just don't see the difference between these two.
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Keypoints are the same thing as interest points. They are spatial locations, or points in the image that define what is interesting or what stand out in the image. They are invariant to image rotation, shrinkage, translation, distortion, and so on.
In computer vision and image processing, a feature is a piece of information about the content of an image; typically about whether a certain region of the image has certain properties. Features may be specific structures in the image such as points, edges or objects.
What are features? Features are parts or patterns of an object in an image that help to identify it. For example — a square has 4 corners and 4 edges, they can be called features of the square, and they help us humans identify it's a square.
Key-points should simply be points (x,y), imo. What describes a point and basically the region around it should be called a descriptor. Some keypoints mix those terms and they become points with an attached description vector, just like @rayryeng explained.
Image features are small patches that are useful to compute similarities between images. An image feature is usually composed of a feature keypoint and a feature descriptor.
The keypoint usually contains the patch 2D position and other stuff if available such as scale and orientation of the image feature.
The descriptor contains the visual description of the patch and is used to compare the similarity between image features.
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