JOURNAL ARTICLE

A Robust Moving Objects Detection Algorithm Based on Gaussian Mixture Model

Abstract

The paper proposes a novel algorithm which can effectively resolve the problems of background disturbance and light changes in allusion to the problem that the background subtraction is sensitive to light changes. The algorithm, combined with the methods of background subtraction and adjacent frame difference, adopts Gaussian mixture model to avoid the impact of background disturbance. By using the idea of adjacent frame difference for reference, it deals with light changes by background reconstruction and constructing the function of dynamic learning efficiency. The algorithm is simulated under the circumstance of background disturbance and light changes, the experimental results show that the algorithm is more efficient and robust than traditional methods, and it can attain background model in the complex condition quickly. The algorithm is particularly suitable to the intelligent video surveillance with static cameras.

Keywords:
Background subtraction Computer science Frame (networking) Algorithm Computer vision Artificial intelligence Mixture model Disturbance (geology) Gaussian network model Gaussian Pixel

Metrics

6
Cited By
0.93
FWCI (Field Weighted Citation Impact)
10
Refs
0.83
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Measurement and Detection Methods
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Remote Sensing and Land Use
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science

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