Extracting key frames (KF) from video is of great interest in many applications, such as video summary, video
organization, video compression, and prints from video. KF extraction is not a new problem. However, current literature
has been focused mainly on sports or news video. In the consumer video space, the biggest challenges for key frame
selection from consumer videos are the unconstrained content and lack of any preimposed structure. In this study, we
conduct ground truth collection of key frames from video clips taken by digital cameras (as opposed to camcorders)
using both first- and third-party judges. The goals of this study are: (1) to create a reference database of video clips
reasonably representative of the consumer video space; (2) to identify associated key frames by which automated
algorithms can be compared and judged for effectiveness; and (3) to uncover the criteria used by both first- and thirdparty
human judges so these criteria can influence algorithm design. The findings from these ground truths will be
discussed.
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