Lucas-Kanade Optical Flow Algorithm Implementation in MATLAB
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The MATLAB-based Lucas-Kanade (LK) optical flow algorithm is a fundamental computer vision technique for analyzing object motion in image sequences. This implementation employs a multi-scale Gaussian pyramid approach, which efficiently handles large displacement motions by processing images at different resolution levels. The algorithm works by minimizing the sum of squared differences between image patches using a least squares method, with key functions including gradient computation, spatial coherence enforcement, and iterative refinement. The package includes standard reference images that facilitate accurate benchmarking and parameter tuning for various computer vision applications. This robust implementation serves as a practical tool for motion analysis, object tracking, and video processing tasks, featuring modular code structure that allows easy customization of parameters like window size, pyramid levels, and convergence thresholds.
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