A PEDESTRIAN TRAJECTORY PREDICTION ALGORITHM BASED ON IMPROVED GAN

In order to accurately predict the future trajectory of pedestrians, a pedestrian trajectory prediction model based on improved GAN is proposed. The model took the observer's camera motion state vector, pedestrian pose information and pedestrian's historical trajectory as input. In the attention module, the motion attention mechanism was used to measure the impact of the observer's camera motion on the pedestrian's trajectory, and the posture attention mechanism was used to extract the hidden features in the human pose. The interactive attention mechanism was used to model the social interaction between pedestrian. The predicted trajectories were obtained through the generative adversarial network. Experimental results show that the proposed model has higher accuracy than the existing algorithms.