Tilt sensor is usually necessary for attitude control of a biped robot when it walks on an uneven terrain. There are many sensors to measure the tilt angles, and gyro sensor is widely used for estimation of tilt angles because it can offer the sufficient bandwidth, so it is suitable for sensing the rapid motions that create high frequency pose variations. However, its major disadvantage is the lack of accuracy and drift over time. Vision sensor can estimate an accurate attitude of robot directly from the image of camera. However, it is hard to control attitude of rapid or abrupt rotation due to the time delay and its low bandwidth. In this paper, we implement a fusion filter frame that combines two sensor signals using Extended Kalman Filter (EKF) to compensate the weakness of two sensors. We use modified track-to-track model as fusion method. The simulation and experimental results show that we obtain the accurate attitude information through fusion filter combining two sensor signals.