期刊文献+

基于多模式均值时空模型的目标融合检测方法 被引量:1

Target Fusion Detection Method Based on Spatiotemporal Multimodal Mean Model
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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。 Target detection is difficuh 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.
出处 《中国图象图形学报》 CSCD 北大核心 2010年第8期1254-1259,共6页 Journal of Image and Graphics
关键词 目标检测 多模式均值时空模型 融合检测 target detection, spatiotemporal multimodal mean model, fusion detection
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参考文献10

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