One basic observation for pedestrian detection in video sequences is that both appearance and motion information are important to model the moving people. Based on this observation, we propose a new kind of features, 3D Haar-like (3DHaar) features. Motivated by the success of Haar-like features in image based face detection and differential-frame based pedestrian detection, we naturally extend this feature by defining seven types of volume filters in 3D space, instead of using rectangle filter in 2D space. The advantage is that it can not only represent pedestrian's appearance, but also capture the motion information. To validate the effectiveness of the proposed method, we combine the 3DHaar with support vector machine (SVM) for pedestrian detection. Our experiments demonstrate the 3DHaar are more effective for video based pedestrian detection.