Investigating keyframe selection methods in the novel domain of passively captured visual lifelogs
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
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The rapid pace of development of Graphic Processor Units (GPUs) in recent years in terms of performance and programmability has attracted the attention of those seeking to leverage alternative architectures for better performance than that which commodity CPUs can provide. In this paper, the potential of the GPU in automatically structuring video is examined, specifically in shot boundary detection and representative keyframe selection techniques. We first introduce the programming model of the GPU and outline the implementation of techniques for shot boundary detection and representative keyframe selection on both the CPU and GPU, using histogram comparisons. We compare the approaches and present performance results for both the CPU and GPU. Overall these results demonstrate the significant potential for the GPU in this domain.