Target Fusion Detection Method Based on Spatiotemporal Multimodal Mean Model

ZHAO Gaopeng; BO Yuming

doi:10.11834/jig.20100813

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Target Fusion Detection Method Based on Spatiotemporal Multimodal Mean Model
Vol. 15, Issue 8, Pages: 1254(2010)
Published Online：25 August 2010，

Published：2010
DOI： 10.11834/jig.20100813
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DOI：

ZHAO Gaopeng, BO Yuming. Target Fusion Detection Method Based on Spatiotemporal Multimodal Mean Model[J]. Journal of Image and Graphics, 2010, 15(8): 1254. DOI： 10.11834/jig.20100813.

摘要

针对复杂环境下的目标检测问题，提出了一种基于背景模型的融合检测方法。首先在多模式均值模型的基础上，构造多模式均值时空模型，结合像素在时空域上的分布信息，改善了模型对非平稳场景较为敏感的缺点，给出了模型更新方法和前景检测方法；然后利用该模型对可见光和红外图像序列分别进行建模和前景检测，给出了一种基于置信度的目标融合检测方法，利用双传感器信息提高检测精度和可靠性。实验结果验证了本文方法的有效性。

Abstract

Target detection is difficult to be realized in complex scenes when there are moving background objects such as trees. In this paper

a new target fusion detection method is proposed based on background model. Firsty

by combining temporal information of per-pixel and the spatial information in the local region

we introduce a variant of multimodal mean model called the spatiotemporal multimodal mean model that is well suited for the non-stationary scenes. Then

the proposed background model is separately used to extract foreground pixels in visible and infrared image sequences

and a fusion detection method based on the confidence map is proposed to get the target detection result. The multi-sensor information can improve the detection precision and handle different environmental conditions. Experiment results demonstrate the effectiveness of the proposed method.