Moving object detection based on Gaussian pyramid
Tiancan Mei · Journal of Central South University(Science and Technology) · 2013
To solve the problem of dynamic background under natural environment when detecting moving objects,a new background difference method based on Gaussian pyramid model was proposed.Firstly,multi-scale decomposition was carried out for image sequence to get multi-resolution images.Then a high and low double thresholds background difference operation was used under different resolutions to get two foreground images by dual-threshold.All the thresholds were obtained automatically according to the environment.At last,difference images in each layer were fused top-down to detect the interested moving objects,and shadows were removed in HSV space.Background model initialization and update method were based on two assumptions,the first one of which is that background points appear with a larger frequency and the second is that the closer to the current frame,the more likely to represent the real background.The results show that the proposed algorithm can be effectively applied to dynamic background environments and can overcome the effect of illumination changes and shadows.Experiments on several standard image sequences demonstrate that the proposed method has high accuracy,robustness and adaptability.It has lower time complexity and can be applied in real-time detection systems.