Gaussian Mixture Model for Background Generation in Video Object Detection

Implementation of Gaussian Mixture Model for background generation in video object detection, featuring adaptive background modeling and foreground segmentation algorithms.

Orthogonal Correlation Object Detection

Orthogonal correlation object detection employs orthogonal correlation methods to identify target positions in images. Suitable for various computer vision applications including video object detection, visual object detection, object localization, visual object tracking, video object tracking, image matching, and image registration. Implementation typically involves calculating correlation matrices between target templates and image regions using orthogonal basis functions.

Building Gaussian Mixture Models (GMM) for Computer Vision Applications

This implementation constructs a Gaussian Mixture Model (GMM) designed for computer vision applications including video object detection, video surveillance, motion detection, moving object detection, and video object tracking. The code features parameter optimization and expectation-maximization algorithm implementation for robust multi-modal data modeling.