Shi-Tomasi Corner Detector

The Harris corner detector performs well in many cases, but it can still be improved. Around six years after the original paper by Harris and Stephens, Shi-Tomasi came up with something better and they called it Good Features To Track. You can read the original paper at: http://www.ai.mit.edu/courses/6.891/handouts/shi94good.pdf. They used a different scoring function to improve the overall quality. Using this method, we can find the N strongest corners in the given image. This is very useful when we don't want to use every single corner to extract information from the image. As discussed earlier, a good interest point detector is very useful in applications, such as object tracking, object recognition, image search, ...

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