Sensor imperfections in the form of photo-response nonuniformity (PRNU) patterns are a well-established fingerprinting technique to link pictures to the camera sensors that acquired them. The noise-like characteristics of the PRNU pattern make it a difficult object to compress, thus hindering many interesting applications that would require storage of a large number of fingerprints or transmission over a bandlimited channel for real-time camera matching. Recently, in [1] we proposed a compact representation of PRNU fingerprints based on a fixed number of quantized random projections, leading to an extremely compact fingerprint representation. Results indicated that random projections sensibly outperform other techniques for fingerprint compression. In this demo, we show two potential applications of the compressed fingerprints, in the form of Camera Identification and large-scale Image Retrieval.