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http://dx.doi.org/10.5573/ieie.2014.51.2.076

Parallel Design and Implementation of Shot Boundary Detection Algorithm  

Lee, Joon-Goo (Dept. of Computer Science, Dan-kook University)
Kim, SeungHyun (Dept. of Computer Science, Dan-kook University)
You, Byoung-Moon (L&Y Vision Technologies, Inc.)
Hwang, DooSung (Dept. of Kinesiologic Medical Science, Dan-kook University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.51, no.2, 2014 , pp. 76-84 More about this Journal
Abstract
As the number of high-density videos increase, parallel processing approaches are necessary to process a large-scale of video data. When a processing method of video data requires thousands of simple operations, GPU-based parallel processing is preferred to CPU-based parallel processing by way of reducing the time and space complexities of a given computation problem. This paper studies the parallel design and implementation of a shot-boundary detection algorithm. The proposed shot-boundary detection algorithm uses pixel brightness comparisons and global histogram data among the blocks of frames, and the computation of these data is characterized with the high parallelism for the related operations. In order to maximize these operations in parallel, the computations of the pixel brightness and histogram are designed in parallel and implemented in NVIDIA GPU. The GPU-based shot detection method is tested with 10 videos from the set of videos in National Archive of Korea. In experiments, the detection rate is similar but the computation time is about 10 time faster to that of the CPU-based algorithm.
Keywords
CUDA; parallel design; GPU; shot-boundary detection;
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Times Cited By KSCI : 1  (Citation Analysis)
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