Pedestrian Recognition Based on Saliency Detection and Kalman Filter Algorithm in Aerial Video

For the problem of low resolution, camera movement and target´s detail fuzzy in aerial video when detecting and recognizing pedestrian, this paper proposes weighted region matching algorithm based on saliency detection and Kalman filter(KS-WRM). In the preprocessing stage, the KS-WRM algorithm uses saliency detection algorithm, which adds human subjective consciousness to segment pedestrians. The result is perfect and improves recognition accuracy. In the matching stage, the KS-WRM algorithm first uses Kalman filter algorithm to label candidate´s region, and then selects candidates using weighted region matching algorithm in labeled region, which can avoid the problem of selecting candidates under supervision. As a result, it not only cuts down calculated amount, but also improves adaptive and real-time ability, then applies successfully in the video field. With a large number of experiments in aerial video of complex environment, it is demonstrated that the proposed method outperforms recent state-of-the-art methods.