Recent developments in proccessing units, memory and storage devices and image processing and computer vision algorithms makes it possible to process large amount of data automatically: using a normal PC, it is possible to store more than a thousand hours of videos in storage devices and process millions of images to find similar images automatically in a second. Also, the mass production and cheap prices of cameras has made it possible to collect large amounts of images and videos without any significant cost. Utilizing such developments, we decided to collect, store and process videos similar to visual input of some subjects and study to what end we can use such a data to help people with limited memories. In other words, our long term goal is to answer the question of What is worth remembering in a data set of every day life videos?

The Free-viewpoint Immersive Networked Experience (FINE) project will be focused on researching and developing a novel end-to-end architecture for the creation and delivery of a new form of live media content. FINE will introduce the concept of live free-viewpoint content which will provide rich and compelling immersive experiences by allowing remote viewers to place a virtual camera in a real live-action scene and move it freely in space and time, heightening their sense of presence and reality.

The goal of this project is to build a 3D reconstruction of the motion of all the players during a professional fooball game. This has numerous potential applications especially for the visualization of the game for spectators and its transmission for broadcastors. And also it would be of great interest to the games industry to obtain high quality motion capture from real games.