With advances in digital camcorders, re-capturing commercial videos called camcorder theft is getting a big problem. In this paper, we propose an automatic detection method for re-captured videos based on the Sensor Pattern Noise(SPN). To discern a re-captured video, a given video is divided into shots first. Several usable shots are selected and SPN is estimated from each of the shots. Using peak-to-correlation energy (PCE), a connection matrix, which indicates which shots were recorded with a specific camcorder, is constructed. Then, false negative connections are corrected by using Warshall`s algorithm. With the number of connections from connection matrix, the given video is determined whether it was the re-captured or not. The experimental results show that the proposed method performs well even with compressed and scaled re-captured videos.
With advances in digital camcorders, re-capturing commercial videos called camcorder theft is getting a big problem. In this paper, we propose an automatic detection method for re-captured videos based on the Sensor Pattern Noise(SPN). To discern a re-captured video, a given video is divided into shots first. Several usable shots are selected and SPN is estimated from each of the shots. Using peak-to-correlation energy (PCE), a connection matrix, which indicates which shots were recorded with a specific camcorder, is constructed. Then, false negative connections are corrected by using Warshall`s algorithm. With the number of connections from connection matrix, the given video is determined whether it was the re-captured or not. The experimental results show that the proposed method performs well even with compressed and scaled re-captured videos.