发明名称 Self-Learning Object Detection and Classification Systems and Methods
摘要 A method of object classification based upon fusion of a remote sensing system and a natural imaging system is provided. The method includes detecting an object using the remote sensing system. An angle of view of a video camera of the natural imaging system is varied. An image including the object is generated using the natural imaging system. The natural imaging system may zoom in on the object. The image represented in either pixel or transformed space is compared to a plurality of templates via a competition based neural network learning algorithm. Each template has an associated label determined statistically. The template with a closest match to the image is determined. The image may be assigned the label associated with the relative location of the object, the relative speed of the object, and the label of the template determined statistically to be the closest match to the image.
申请公布号 US2010215254(A1) 申请公布日期 2010.08.26
申请号 US20090392379 申请日期 2009.02.25
申请人 TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA 发明人 PROKHOROV DANIL V.
分类号 G06K9/62;G08G1/123 主分类号 G06K9/62
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