Improvement of the Gaussian Mixture Model Based on EmguCV Motion Target Detection Design

Introduces a kind of video moving object detection based on mixture Gaussian model design, mainly combined with frame difference method and the Gaussian mixture model, then use K-means clustering algorithm, for complex scenarios different update rate is realized by using different background region, to complete the moving target detection, respectively, compared to traditional Gaussian mixture model (Gaussian mixture model, GMM) and the traditional frame difference detection method, in order to better solve the problem of motion target detection in complex scene, and mainly analyze based on frame difference and EmguCV framework, and finally using C# and EmguCV framework for moving targets detection. Application through the experiment show that the design is easy to use, and the performance is better.