Real-time video breakup detection for multiple HD video streams on a single GPU

Jakub Rosner, Hannes Fassold, Martin Winter, Peter Schallauer
SPIE real-time image and video processing, 2012



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An important task in film and video preservation is the quality assessment of the content to be archived or reused out of the archive. This task, if done manually, is a straining and time consuming process, so it is highly recommended to automate this process as far as possible. In this paper, we show how to port a previously proposed algorithm for detection of severe analog and digital video distortions (termed “video breakup”), efficiently to NVIDIA GPUs of the Fermi Architecture with CUDA. By parallizing of the algorithm massively in order to take usage of the hundreds of cores on a typical GPU and careful usage of GPU features like atomic functions, texture and shared memory, we achive a speedup of roughly 10–15 when comparing the GPU implementation with an highly optimized, multi-threaded CPU implementation. Thus our GPU algorithm is able to analyze nine Full HD (1920 x 1080) video streams or 40 standard definition (720 x 576) video streams in real-time on a single inexpensive Nvidia Geforce GTX 480 GPU. Additionally, we present the AV-Inspector application for video quality analysis where the video breakup algorithm has been integrated.
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