3D Reconstruction for Traffic Surveillance
Hanna Källén
In order to get good knowledge of the safety of a traffic intersection, a video camera is placed at the intersection. Video from this camera can then be used to automatically track the vehicles in the intersection. The purpose of this master's thesis is to develop an algorithm for building 3D models of vehicles from such video. The goal is to use the reconstructions to calculate the distance between road users in the intersection to find out how dangerous the intersection is.
To determine how good a certain reconstruction is, the largest reprojection error is considered, that means that the error is measured in the L-infinity norm. Between different frames in the video, the vehicles have moved and rotated. Given the rotation, finding the optimal reconstruction is a quasi-convex problem and can be solved efficiently. Since the rotation is not known, a branch and bound algorithm has been implemented. The branch and bound algorithm search through possible rotations and selects the one that gives the best result. To evaluate the algorithm, reconstructions of a bus and two different cars driving through the intersection have been made with good results.
Questions: webmaster
Senast uppdaterad: 2009-04-01
