Meaningful automatic video demultiplexing with unknown number of cameras, contrast changes, and motion

This paper presents a software-based parameter-free method for the demultiplexing of a video stream (L. Rudin et al., 2004) that is missing camera labeling information. The method is based on the observation that frames coming from the same input camera share some common characteristic features. These features are extracted from the input frames and grouped together according to statistical criteria. As a result of this grouping the number of different input sources in the video stream is inferred and it is possible to ascertain the source for each frame.