A robust technique for person-background segmentation in video sequences based on the codebook method of background subtraction and head tracking

In this paper, we introduce a new method to reliably ex- tract humans from a video sequence even when the humans are static for long periods of time. The proposed method addresses a common problem in background subtraction techniques whereby humans that are static are mistaken for new additions to the background scene and are consequently absorbed into the background model. In the proposed method, codebook background subtraction is used to identify foreground regions in the video frame. A motion based particle filter is then used to track one or more human heads in the frame and determine which of these foreground regions represent people. The background model is then selectively updated given this knowledge thus ensuring that people will never be absorbed into the background model once detected, even when indefinitely static. Simulation results confirm that a human body is robustly extracted using this method in a non-static environment.