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Interest in automatic crowd behaviour analysis has grown considerably in the last few years. Crowd behaviour analysis has become an integral part all over the world for ensuring peaceful event organizations and minimum casualties in the places of public and religious interests. Traditionally, the area of crowd analysis was computed using handcrafted features. However, the real-world images and videos consist of nonlinearity that must be used efficiently for gaining accuracies in the results. As in many other computer vision areas, deep learning-based methods have taken giant strides for obtaining state-of-the-art performance in crowd behaviour analysis. This paper presents a comprehensive survey of current convolution neural network (CNN)-based methods for crowd behaviour analysis. We have also surveyed popular software tools for CNN in the recent years. This survey presents detailed attributes of …