Explore MATLAB source code curated for "欧式距离" with clean implementations, documentation, and examples.
My graduation project featuring MATLAB-based key frame extraction code, enhanced with optical flow method references. The implementation utilizes Euclidean distance, mean, variance, and coefficient of variation metrics for frame difference analysis. The thoroughly debugged code produces optimal results and is shared here for community benefit.
KNN k-Nearest Neighbors algorithm implementation supporting both Euclidean and Manhattan distance metrics for classification and regression tasks, with configurable k-value parameter.
ISODATA Clustering Algorithm Demonstration Program implemented strictly according to Algorithm 3 in Section 2.4.4 "Dynamic Clustering Method" from Sun Jixiang's "Modern Pattern Recognition". Uses Euclidean distance as the measurement metric with configurable distance thresholds and cluster merging/splitting parameters.
For two sets of 3D point clouds, transformation error can be computed using Euclidean distance after coordinate transformation, with implementations involving point cloud registration algorithms and error metrics calculation.