Considering requirements of real-time and robustness of detection algorithm in moving object detection process under dynamic background

a moving object detection algorithm based on binary robust invariant scalable keypoints（ BRISK） is proposed. The improved BRISK algorithm is used to detect feature points. To assure matching precision and speed

the k nearest neighbor（ KNN） algorithm is adopted to match feature points. Global motion parameter estimation method based on random sample consensus（ RANSAC） is used to obtain the optimal global motion parameters. Interframe difference method is applied to achieve the detection of moving targets. The experimental results indicate that the improved BRISK algorithm reduces the number of feature points by 49. 8%

and KNN algorithm removes 85. 9% feature points. Meanwhile

the algorithm can accurately detect moving obiects in various scenes

compared with previous algorithm

detecting effect is better.