Perceptual Computing in general and Computer Vision in particular have great potentials to change the way we interact with computers and how machines such as robots perceive the world. Over the last three decades significant progress has been made in computer vision. Today it is possible to use image information for quality control and domain specific problems such as face recognition, recovery of CAD models for well-defined objects and basic visual surveillance. Robustness of perception and vision algorithms however is a notorious problem and one of the major bottlenecks for industrial applications. At the same time there is little doubt that in the next decades small and inexpensive sensors will be developed and embedded in many devices. Our hypothesis is that the integration of multiple features and sensors facilitates robustness in environments of realistic complexity.
To acquaint students with the IT Sector, by imparting quality education to them in the field of Information Technology through state of the art infrastructure and to allow students to take best advantage of their educational opportunities for career development.
To train and develop IT professionals with confidence, competence, commitment and character.