Abstract
The fast evolution of digital media, in special digital videos, has created an exponential growth of data, increasing the storage and transmission cost and the video content retrieve information complexity. Video summarization has been proposed to circumvent some of these issues and also serves as a pre-processing step in many video applications. In this paper, a static video summarization algorithm is studied and in order to reduce its high execution time, parallelizations using Graphics Processor Units (GPUs) and multicore CPUs are proposed. We also explore a hybrid approach combining both hardware to maximize the performance. The experiments were performed using 120 videos varying frame resolution and video length and the results showed that the hybrid and the multicore CPUs versions reached the best executions times, achieving 4× speedup in average.
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Almeida, S.S., Cayllahua-Cahuina, E., de A. Araújo, A., Cámara-Chávez, G., Menotti, D. (2014). GPUs and Multicore CPUs Implementations of a Static Video Summarization. In: Bayro-Corrochano, E., Hancock, E. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2014. Lecture Notes in Computer Science, vol 8827. Springer, Cham. https://doi.org/10.1007/978-3-319-12568-8_116
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DOI: https://doi.org/10.1007/978-3-319-12568-8_116
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