Title :
A novel motion object detection method based on improved frame difference and improved Gaussian mixture model
Author :
Yu Xiaoyang ; Yu Yang ; Yu Shuchun ; Song Yang ; Yang Huimin ; Liu Xifeng
Author_Institution :
Higher Educ. Key Lab. for Meas. & Control Technol. & Instrum. of Heilongjiang Province, Harbin Univ. of Sci. & Technol., Harbin, China
Abstract :
The existing motion detection methods include background subtraction and frame difference. But it is prone to exist some holes with frame difference method and it is difficult to build background model using background subtraction method. So the test results did not achieve the ideal state. Aim at these problem, this paper combines frame difference method improved by motion history image with background subtraction method based on improved Gaussian mixture model to detect the motion object. The experimental results show the method has achieved a satisfactory effect.
Keywords :
Gaussian processes; image motion analysis; object detection; Gaussian mixture model improvement; background model; background substraction method; frame difference improvement; motion history image; motion object detection method; Adaptation models; Motion segmentation; Robustness; Gaussian mixture model; frame difference; motion detection; spatio-temporal combination;
Conference_Titel :
Measurement, Information and Control (ICMIC), 2013 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4799-1390-9
DOI :
10.1109/MIC.2013.6757972