Pedestrian target tracking based on the UAV platform can be widely used in traffic control, field search, and military reconnaissance. It is an important research task of computer vision and intelligent cruise. Aiming at the limitations of the UAV surveillance system in moving pedestrian target tracking, such as background change, pedestrian deformation, occlusion interference, and lack of real-time performance, the dual Kalman filter is used to improve the traditional TLD tracking algorithm, the proposed method can accelerate the correction of the predicted detection area, reduce the disturbance of the environment background and the target deformation to the pedestrian tracking accuracy, and reduce the detection time by using the adaptive adjustment method of the detection area to offset the time cost caused by double Kalman filtering, to improve the Algorithm’s real-time performance. The test results show that the proposed method has high accuracy, stability, and real-time performance in pedestrian target tracking based on the UAV platform.
Experimental program is designed to analyze the radiation and absorption characteristic of the sky background at near-infrared Oxygen A absorption band of passive ranging based on Oxygen spectral absorption; an acousto-optic tunable hyper spectral imaging spectrometer is used as the measuring device. Under the condition of sunny, cloudy, and snowy weather, the sky background spectral distribution is collected using the acousto-optic tunable hyper spectral imaging spectrometer. Then the Oxygen absorption rate is calculated according to the principle of Oxygen spectrum absorption passive ranging. The measurement result shows: absorption lines exist in the sky background spectral distribution at the Oxygen A absorption band, and the absorption rates are different at different weather conditions. The Oxygen absorption rates are the biggest under snowy weather, bigger under cloudy weather, and the smallest under sunny weather. The general change pattern of Oxygen absorption rate under different weather conditions is obtained and the result has laid solid foundation for suppressing the interference of the background and extracting target spectral accurately in subsequent passive ranging researching.
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