In Nuclear Safeguards, surveillance cameras monitor the correct processing of nuclear material. Nuclear inspectors are faced with tens of thousands of images to review, of which less than 1% is significant. Besides the reduction of the standard two-frame differencing filter, we further limit the image set to review by tracking on the distribution of image time-stamps. Traditional visual tracking cannot be applied, owing to the low frame rate, and the need for compatibility with the standard change detection algorithm. Our algorithm is based on a HMM model of the nuclear process, and handles multiple flasks and observations available only when the flasks are moved. The model makes use of descriptive statistics of the durations of processing stages to refine the HMM predictions.