This paper addresses the problem of video anomaly recovery from a sequence of spectrally compressed video frames. Analysis of anomalies occurring in both time and spectrum is important in video surveillance applications. We present a methodology for the recovery of anomalies such as moving objects and their spectral signatures from spectrally compressed video. The spectrally compressed video frames are obtained by using a Coded Aperture Snapshot Spectral Imaging (CASSI) system. The CASSI system encodes a 3-D data cube containing both 2-D spatial information and spectral information in a single 2-D measurement. In the proposed methodology, we use the spectrally compressed video as columns of a large data matrix GGG. Principal Component Pursuit (PCP) is then used to decompose GGG into the stationary background and a sparse matrix capturing the anomalies in the foreground. The sparse matrix is then used jointly with GGG to recover the spectral information of the objects of interest. An e...
Ana B. Ramirez, Henry Arguello, Gonzalo R. Arce