Gaussian Mixture Model for River Region Classification

Abstract

This report proposes a river region classification using a Gaussian mixture model for feature vectors. The conventional method classifies river region by assuming a single Gaussian distribution. Since this work assumes a Gaussian mixture distribution, better classification performance can be expected because it becomes possible to approximate more complex distributions than any single Gaussian. Experimental results with real surveillance videos are shown for evaluating the performance of the proposed method, and improvement of the performance from the conventional method in term of precision is verified.