Occlusions in Camera Networks and Vision:The Bridge between Topological Recovery and Metric ReconstructionbyEdgar J. LobatonDoctor of Philosophy in Engineering-Electrical Engineering and Computer SciencesUniversity of California, BerkeleyProfessor S. Shankar Sastry, Chair Camera networks are widely used for security and tracking. Knowledge of camera locationsand geom...

Networks of cameras such as building security systems can be a source of localization information for a mobile robot assuming a map of camera locations as well as calibration information for each camera is available. This thesis describes an automated system to acquire such information. A fully automated camera calibration system uses fiducial markers and a mobile robot in order to drastically ...

One of the fundamental requirements for visual surveillance using non-overlapping camera networks is the correct labeling of tracked objects on each camera in a consistent way, in the sense that the captured tracklets, or observations in this paper, of the same object at different cameras should be assigned with the same label. In this paper, we formulate this task as a Bayesian inference probl...

Camera networks are widely used for tasks suchas surveillance, monitoring and tracking. In or-der to accomplish these tasks, knowledge of lo-calization information such as camera locationsand other geometric constraints about the envi-ronment (e.g. walls, rooms, and building layout)are typically considered to be essential. How-ever, this information is not always req...

Most face recognition and tracking techniques employed in surveillance and human-computer interaction (HCI) systems rely on the assumption of a frontal view of the human face. In alternative approaches, knowledge of the orientation angle of the face in captured images can improve the performance of techniques based on non-frontal face views. In this paper, we propose a collaborative technique f...