In this work the goal is to develop a distributed system for sensing, interpreting and visualizing the real-time dynamics of urban life within the 3D context of a city focusing on typical, useful dynamic information such as walking pedestrians and moving vehicles captured by pan-tilt-zoom (PTZ) video cameras. Three-dimensionalization of the data extracted from video cameras is achieved by an algorithm that uses the Manhattan structure of the urban scene to automatically estimate the camera pose. Thus, if the pose of the video camera changes, our system will automatically update the corresponding projection matrix to maintain accurate geo-location of the scene dynamics.
['Eduardo R. Corral-Soto', 'Ron Tal', 'Larry Wang', 'Ravi Ancil Persad', 'Luo Chao', 'Chan Solomon', 'Bob Hou', 'Gunho Sohn', 'James H. Elder']
3DTown: The automatic urban awareness project