For a camera moving through the environment we frequently wish to track particular world points from one frame to the next. We’ll do a quick introduction to the very large field of feature detection and matching using Harris corner features.
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When matching points between scenes with large different viewpoints we need to account for varying image size and rotation. SIFT features are a powerful way to achieve this.
Let’s recap the important points from the topics we have covered in advanced image processing.
Why do robots need a sense of vision in this modern age when GPS satellites can tell a robot where it is? Let’s talk about GPS, how it works and its strengths and weaknesses such as multipath and urban canyon effects.
We summarise the important points from this lecture.