In the UAV path planning study, due to the relative movement of multiple targets and the UAV, long-term and large-scale UAV, autonomous tracking has not been achieved. Therefore, aiming at this problem, this paper uses radar to provide a real-time feedback on target position, estimates the later motion state of the target according to its position, and then perform dynamic path planning by combining the feedback data and the state estimation result. Finally, The UAV path is optimized in real time. Experiments show that the proposed scheme can better plan the UAV path when multiple targets are in motion, thus improving the intelligence of the UAV and the capability of long time tracking.

A novel content-aware image resizing mechanism based on composition detection and composition rules is proposed to address the lack of esthetic perception in current content-aware resizing algorithms. A composition detection module is introduced for the detection of the composition of the input image types in the proposed algorithm. According to the classification results, the corresponding composition rules in computational esthetics are selected. Finally, the algorithm performs the operations of seam carving using the corresponding esthetic rules. The resized image not only protects the important content of the image, but also meets the composition rules to optimize the overall visual effect of the image. The simulation results show that the proposed algorithm achieves a better visual effect. Compared with the existing algorithms, the proposed algorithm not only effectively protects important image content, but also protects important structures and improves the overall beauty of the image.