Driver behaviour recognition based on the fusion of head movement and hand movement
Abstract
Accurate recognition of non-driving activity (NDA) is important for the design of intelligent human–machine interface to achieve a smooth and safe control transition in the conditionally automated driving vehicle. However, some characteristics of such activities such as limited-extent movement and similar background pose a challenge to the existing 3D convolutional neural network–based action recognition methods. In this chapter, a dual-stream 3D residual network, named DS3D ResNet, has been proposed to enhance the learning of spatio-temporal representation and improve the performance of activity recognition. Specifically, a parallel 2-stream ...
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