Abstract
We have proposed the real-time estimation method of pedestrian density in video sequences. The proposed method extracts moving regions from video sequences based on background difference and inter-frame difference, and estimates the number of pedestrians from the size of the extracted region, using conversion function constructed from the prior-learned statistical data. One existing problem in the proposed method is that we utilize the conversion function constructed in an ad-hoc manner. In this paper, we introduce the simple model for the relationships between the moving region size and the number of pedestrians in the region, and construct the conversion function from the model. We evaluate the effectiveness of the proposed approach by comparison the estimated values with the true values and find that the proposed method in this paper can decrease the mean squared error by up to 32%.
