The invention provides a
pedestrian behavior intention prediction method based on multi-
task learning. The method comprises the following steps: a training sample set is constructed; a
pedestrian behavior intention prediction model is constructed by using the basic network, the attitude detection network and the intention recognition network, the basic network takes a
single frame image in the training sample set as input, image features are extracted, and a feature map is obtained; an
encoder part of the attitude detection network comprises a part intensity field sub-network and a part association field sub-network which respectively take the feature map as input and take the joint feature map and the skeleton feature map as output, and a decoder part of the attitude detection network obtains a
pedestrian attitude image according to the joint feature map and the skeleton feature map; the intention recognition network takes the feature map as input and takes the
pedestrian behavior intention image as output; and the
pedestrian behavior intention prediction model is trained, and the
pedestrian behavior intention is predicted by using the pedestrian behavior intention prediction model. According to the method, a pedestrian
detector does not need to be adopted, each pixel is processed separately, the
running time is constant, and the prediction effect meets the requirement.