Abstract
Based on the optical flow technology, a convolutioal neural network (CNN) is proposed for nursing-care robots to perform the behavior recognition task, which considered both static and dynamic information during human motions, thus it is more accurate than the traditional CNN. Firstly, a behavior processing method, combining with Lucas-Kanade optical flow technology, is elaborately designed and tested. In this method, the limitation of static processing method existed in CNN is solved well, then the method is applied to a CNN model for behavior recognition task. Simulation experiment has been carried out, indicating that this method can achieve a higher recognition accuracy and obtain a good recognition effect successfully.
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Zhang, X., Liu, H., Zhang, M. (2018). A New Behavior Recognition Method of Nursing-Care Robots for Elderly People. In: Qiao, F., Patnaik, S., Wang, J. (eds) Recent Developments in Mechatronics and Intelligent Robotics. ICMIR 2017. Advances in Intelligent Systems and Computing, vol 690. Springer, Cham. https://doi.org/10.1007/978-3-319-65978-7_82
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DOI: https://doi.org/10.1007/978-3-319-65978-7_82
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