Video anomaly recovery from compressed spectral imaging

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 Q. Principal Component Pursuit (PCP) is then used to decompose Q into the stationary background and a sparse matrix capturing the anomalies in the foreground. The sparse matrix is then used jointly with Q to recover the spectral information of the objects of interest. An example for the recovery of video anomalies in a 3-channel spectral video system (RGB) is presented.