Method for estimating number of persons based on deep learning

The invention discloses a method for estimating the number of persons based on deep learning, and belongs to the population density estimation based on deep learning. According to the invention, the method comprises the steps: employing a single-column convolution neural network based on a convolution layer and a pooling layer; learning the population features through the training of a large number of samples, estimating the population density map of an input image, carrying out the integration of the density map, and achieving the estimation of the number of persons on the image. Compared with other conventional deep learning algorithm, the convolution neural network employed in the invention is simple in structure, is low in complexity, is short in training time, and is higher in estimation precision. 本发明公开了种基于深度学习的人数估计方法，属于基于深度学习的人群密度估计。本发明采用种基于卷积层和池化层的单列卷积神经网络，通过大量样本的训练，学习人群特征，从而估计输入图像的人群密度图，进而对密度图进行积分，得到该图像上人群的人数估计。对比目前的其他深度学习算法，本发明所采用的卷积神经网络，结构简单，复杂度低，训练时间短，且估计精确度更高。