אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

One of the principal goals of Computer Vision is to build artificial systems that are able to perceive and understand the world, obtaining information from images acquired by one or more cameras. The same objective, extended to generic sensors, can be found in Robotics, where autonomous robots require a complete knowledge of the environment to provide services and perform tasks as planning, obstacles avoidance or objects grasping. During this talk I will present a novel approach for Visual Simultaneous Localization And Mapping that allows to improve both the accuracy and the robustness of the current state of the art solutions and, at the same time, to model accurately the uncertainty involved in the process. In particular I will propose to adopt a new map element parametrization to reduce the non linearity of the 3D reconstruction and the use of a framework, called Uncertain Projective Geometry, to detect moving elements in the scene or estimate more complex structures