To solve the generation and update of background model in moving target detection,firstly, an approach to background generation based on modified K-means clustering algorithm was proposed in this paper.

Then analyzes and classifies the RGB value per pixel of the sequence and uses the average RGB value of the class which has the highest frequency in the sequence to construct the background model.

A moving object detection algorithm based on background modeling is proposed for video surveillance system with static camera.

A novel background modeling method based on color grade of different frames;

New method for background modeling and moving object detection based on clustering;

Analysis of Robust Background Modeling Techniques for Different Information Levels

Detection method for moving small target in infrared image sequences with dynamic background;

Face detection under complex and dynamic background;

A Dynamic Background-based Moving Vehicle Tracking Algorithm;

Firstly, moving pixels was extracted by using difference image algorithm, then motion object and moving background were distinguished by the change frequency of pixel state.