Pedestrian detection based on improved Gaussian mixture model
Liya Yang · Journal of Jilin University · 2011
Aiming at the peculiarity of pedestrian in the road traffic, an effective pedestrian detection method was proposed based on an improved Gaussian mixture model(GMM) in 3 aspects: parameter updating, background estimation and foreground segmentation. The possibility of misjudging the static foreground as the background was reduced using a parameter updating model based on the image segmentation. The time of the foreground merging into the background was controlled applying the adjustment scheme of foreground merging time.The foreground segmentation condition was optimized by introducing the concept of average weight. The test results showed that the improved algorithm is better than the traditional GMM. It is characterized by good robustness and adaptability, able to detect the slow-moving even static pedestrian.