Work

Dynamic Control of Adaptive Mixture-of-Gaussians Background Model

Year: 2006

Type: conference-paper

Abstract: We propose a method for create a background model in non-stationary scenes. Each pixel has a dynamic Gaussian mixture model. Our approach can automatically change the number of Gaussians in each pixel. The number of Gaussians increases when pixel values often change because of Illumination change, object moving and so on. On the other hand, when pixel values are constant in a while, some Gaussians are eliminated or integrated. This process helps reduce computational time. We conducted experiments to investigate the effectiveness of our approach.

Source: IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)

DOI: 10.1109/avss.2006.44

Authors: Atsushi Shimada, Daisaku Arita, Rin-ichiro Taniguchi

Institution: Kyushu University

Language: English

Topic: Video Surveillance and Tracking Methods

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W1963524043

FWCI: 4.481

Cites: 8

Cited by: 94

Related to: 10