A Moving Object Detection Algorithm Based on Improved Gaussian Mixture Model

Huai-zhi Ma (), Li-na Gong and Jin-qian Yu
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Huai-zhi Ma: Zaozhuang University
Li-na Gong: Zaozhuang University
Jin-qian Yu: Zaozhuang University

A chapter in Proceedings of 20th International Conference on Industrial Engineering and Engineering Management, 2013, pp 399-408 from Springer

Abstract: Abstract An improved algorithm was proposed to overcome the deficiency in the object detection of intelligent monitoring system. In order to adapt more quickly to the background changes, a global change factor was put forward for the model parameter update rate through the recent time adjacent frame differencing. In the foreground detection stage, in the view of differences between the background disturbance scene and the object-confused scene, two kinds of adaptive detection threshold were introduced which were both composed of weight quadratic sum, and then test result was corrected using short-term variance. Experimental results showed that the algorithm had better adaptability.

Keywords: Adaptive threshold; Gaussian mixture model; Global change factor; Intelligent monitoring; Short-term variance (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-40063-6_40

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DOI: 10.1007/978-3-642-40063-6_40

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