The invention provides a method carrying out target positioning through active adjustment of a camera in an image acquisition application and belongs to the mode identification technology field and the active camera positioning technology field. The method comprises steps that a depth neural network for evaluating the camera positioning effect is trained; multiple times of target positioning tests are carried out, in a positioning test process, a depth neural network for fitting a reinforcement learning value function is trained, and quality of seven types of operation including upward turn, downward turn, leftward turn, rightward turn, amplification, reduction and no change of the camera is determined through the depth neural network; decision for camera operation is made through employing a decision network according to the image information presently acquired by the camera. Through the method based on depth reinforcement learning, image acquisition quality is improved, different target positioning tasks can be adapted to, the method is an autonomous learning positioning method, artificial participation stages are quite few, and the method refers to a method of active camera learning and autonomous target learning.