Abstract: For effectiveness of privacy protection and efficiency of copy detection on large video datasets,a fully GPU-based incremental copy detection scheme is proposed.When a newly added video arrives into the database,GPU on-chip decoder is called for video stream decoding.At the same time,high dimensional SIFT features are extracted on the frame in real-time,which is followed by an incremental K-means clustering method responding to the dynamic database used to update visual words codebook.Then,each frame is represented with a visual words frequency vector.Finally,a spatiotemporal sequence matching method based on visual words representation at frame level is used to determine whether the query is a copy.Experimental results show that our GPU implementation achieves up to a 63 times speedup over the CPU version.