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

Volume

01

fYear

2013

fDate

16-18 Aug. 2013

Firstpage

309

Lastpage

313

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Measurement, Information and Control (ICMIC), 2013 International Conference on

Conference_Location

Harbin

Print_ISBN

978-1-4799-1390-9

Type

conf

DOI

10.1109/MIC.2013.6757972

Filename

6757972