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Segmentation by model fitting in computer vision involves partitioning images based on mathematical representations of different regions, utilizing techniques like the Hough Transform for shape detection and various fitting methods for lines and curves. Key approaches include Least Squares and RANSAC for line fitting, as well as probabilistic methods such as Bayesian inference and Gaussian Mixture Models for handling uncertainty and noise. Tracking objects over time is achieved through Linear Dynamic Models

Author

rameshdevalla144

Language

EN