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Adaptive key SURF feature extraction and application in unmanned vehicle dynamic object recognition 被引量:1
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作者 杜明芳 王军政 +2 位作者 李静 李楠 李多扬 《Journal of Beijing Institute of Technology》 EI CAS 2015年第1期83-90,共8页
A new method based on adaptive Hessian matrix threshold of finding key SRUF ( speeded up robust features) features is proposed and is applied to an unmanned vehicle for its dynamic object recognition and guided navi... A new method based on adaptive Hessian matrix threshold of finding key SRUF ( speeded up robust features) features is proposed and is applied to an unmanned vehicle for its dynamic object recognition and guided navigation. First, the object recognition algorithm based on SURF feature matching for unmanned vehicle guided navigation is introduced. Then, the standard local invariant feature extraction algorithm SRUF is analyzed, the Hessian Metrix is especially discussed, and a method of adaptive Hessian threshold is proposed which is based on correct matching point pairs threshold feedback under a close loop frame. At last, different dynamic object recognition experi- ments under different weather light conditions are discussed. The experimental result shows that the key SURF feature abstract algorithm and the dynamic object recognition method can be used for un- manned vehicle systems. 展开更多
关键词 dynamic object recognition key SURF feature feature matching adaptive hessianthreshold unmanned vehicle
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