Abstract
Vision positioning system is widely used in robotics, industrial testing, servo control and other autonomous systems. Precise object positioning needs to accurately match the feature key points of the object, so as to solve the object position and attitude precisely. Simple image or feature matching method cannot meet the requirements of both reliability and accuracy for positioning system. Recently, deep learning has aroused widespread concern, Caffe as a framework for deep learning, performs particularly well in image recognition. In this paper, we propose a method of using convolutional neural networks to recognize target in complex scenes, and then to obtain the information of the target position by precise image matching. The experimental results show that the proposed method effectively eliminates the false target recognition and improves the image matching accuracy.
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