TY - JOUR AU - Cheung, Sen-Ching S. AU - Kamath, Chandrika PY - 2005 DA - 2005/08/25 TI - Robust Background Subtraction with Foreground Validation for Urban Traffic Video JO - EURASIP Journal on Advances in Signal Processing SP - 726261 VL - 2005 IS - 14 AB - Identifying moving objects in a video sequence is a fundamental and critical task in many computer-vision applications. Background subtraction techniques are commonly used to separate foreground moving objects from the background. Most background subtraction techniques assume a single rate of adaptation, which is inadequate for complex scenes such as a traffic intersection where objects are moving at different and varying speeds. In this paper, we propose a foreground validation algorithm that first builds a foreground mask using a slow-adapting Kalman filter, and then validates individual foreground pixels by a simple moving object model built using both the foreground and background statistics as well as the frame difference. Ground-truth experiments with urban traffic sequences show that our proposed algorithm significantly improves upon results using only Kalman filter or frame-differencing, and outperforms other techniques based on mixture of Gaussians, median filter, and approximated median filter. SN - 1687-6180 UR - https://doi.org/10.1155/ASP.2005.2330 DO - 10.1155/ASP.2005.2330 ID - Cheung2005 ER -