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The explosive growth of user-generated video presents opportunities and challenges. The videos may possess valuable information that was once unavailable. On the other hand, the information may be buried or difficult to access with traditional methods. Automatic keyframe video summarization technologies exist that attempt to address this problem. A keyframe summary can often be viewed quicker than the underlying video. However, a theoretical framework for objectively assessing keyframe summary quality has been absent. The work presented here bridges this gap by presenting a semantically high-level, stakeholder-centered evaluation frame-work. The framework can capture common stakeholder concerns and quantitatively measure the extent to which they are satisfied by keyframe summaries.With this framework, keyframe summary stakeholders and algorithm developers can now identify when success has been achieved. This work also develops a number of novel keyframe summarization algorithms and shows, using the evaluation framework, that they outperform baseline methods. http://archive.org/details/automatickeyfram1094542614 Lieutenant, United States Navy Approved for public release; distribution is unlimited.