Mean-shift

Mean-shift is a clustering technique used to identify groups within data. It works by placing a window around a data point and calculating the average (mean) position of all points within that window. The window then shifts toward this average, and the process repeats until the window stabilizes, indicating a peak or cluster. Essentially, it "shifts" towards areas with higher data density, helping to find natural groupings without predefined numbers of clusters. It's useful for tasks like image segmentation and object tracking, adapting smoothly to the data's structure.