Сравнение методов

	Теория пространственно-масштабных представлений	Детектор углов Харриса
Область	Компьютерное зрение	Компьютерное зрение
Семейство	Machine learning	Machine learning
Год появления	1983	1988
Автор метода	Andrew Witkin and Tony Lindeberg	Chris Harris and Mike Stephens
Тип	Theoretical framework for multi-scale processing	Interest point detector
Основополагающий источник	Lindeberg, T. (1994). Scale-space theory: A basic tool for analyzing structures at different scales. Journal of Applied Statistics, 21(2), 225–270.	Harris, C., & Stephens, M. (1988). A combined corner and edge detector. Alvey Vision Conference, 147–152.
Другие названия	Multi-scale analysis, Gaussian scale-space	Harris Corner Detector, Harris-Stephens Detector, Plessey Operator
Связанные	5	5
Сводка	Scale-space theory, developed by Witkin and Lindeberg, provides a principled mathematical framework for analyzing images at multiple scales simultaneously. By treating scale as an explicit dimension and using Gaussian blurring, scale-space theory enables detection and analysis of features at appropriate scales, solving the fundamental problem of 'which scale should I analyze at?'	The Harris corner detector, introduced by Chris Harris and Mike Stephens in 1988, is a foundational method for identifying corners and interest points in digital images. Harris corners are points where two edges meet at a significant angle, making them stable and repeatable features for image analysis, matching, and 3D reconstruction.