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首页> 外文会议>Conference on Object Detection, Classification, and Tracking Technologies Oct 22-24, 2001, Wuhan, China >An object recognition approach based on feature fusion
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An object recognition approach based on feature fusion

机译：基于特征融合的目标识别方法

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摘要

Multi-sensor information fusion plays an important pole in object recognition and many other application fields. Fusion performance is tightly depended on the fusion level selected and the approach used. Feature level fusion is a potential and difficult fusion level though there might be mainly three fusion levels. Two schemes are developed for key issues of feature level fusion in this paper. In feature selecting, a normal method developed is to analyze the mutual relationship among the features that can be used, and to be applied to order features. In object recognition, a multi-level recognition scheme is developed, whose procedure can be controlled and updated by analyzing the decision result obtained in order to achieve a final reliable result. The new approach is applied to recognize work-piece objects with twelve classes in optical images and open-country objects with four classes based on infrared image sequence and MMW radar. Experimental results are satisfied.
机译：多传感器信息融合在目标识别和许多其他应用领域中起着重要的作用。融合性能紧密取决于所选择的融合级别和所使用的方法。尽管可能主要存在三个融合级别，但特征级别融合是一个潜在且困难的融合级别。针对特征级融合的关键问题，提出了两种方案。在特征选择中，开发的一种正常方法是分析可以使用的特征之间的相互关系，并将其应用于订购特征。在对象识别中，开发了一种多级识别方案，可以通过分析所获得的决策结果来控制和更新其过程，从而获得最终的可靠结果。该新方法被用于基于红外图像序列和MMW雷达识别光学图像中具有12类的工件对象以及具有4类的开放国家对象。实验结果令人满意。

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