光流法opencvppt課件-展示頁
2025-05-15 04:04本頁面
【正文】 Feature Finding and Optical Flow ? A brief mathematical discussion. ? OpenCV Implementation of Optical Flow ? Step by step. Optical Flow: Overview ? Given a set of points in an image, find those same points in another image. ? or, given point [ux, uy]T in image I1 find the point [ux + δx, uy + δy]T in image I2 that minimizes ε: ? (the Σ/w’s are needed due to the aperture problem) ? ?? ???????????xxxxyyyywuwuxwuwuyyxyx yxIyxI ),(),(),( 21 ?????Optical Flow: Utility ? Tracking points (“features”) across multiple images is a fundamental operation in many puter vision applications: ? To find an object from one image in another. ? To determine how an object/camera moved. ? To resolve depth from a single camera. ? Very useful for the 223b petition. ? Determine motion. Estimate speed. ? But what are good features to track? Finding Features: Overview ? Intuitively, a good feature needs at least: ? Texture (or ambiguity in tracking) ? Corner (or aperture problem) ? But what does this mean formally? ? Shi/Tomasi. Intuitive result really part of motion equation. High eigenvalues imply reliable solvability. Nice! ??????????????????????????????????????????odn ei g h b o r h oodn ei g h b o r h oodn ei g h b o r h oodn ei g h b o r h oyyxyxx I I
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