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This paper presents a novel real-time surveillance video summarization system that employs the eye-gaze positions of the surveillance operator. The system output can be used to efficiently review the overlooked sections of the surveillance video, which increases the reliability of the surveillance system. The summary of the operator-monitored actions can also be obtained for efficient re-examination of the surveillance videos. The system employs a novel non-linear video abstraction method that can mix actions from different frames into the same summary frame for more compact videos. The video summaries are performed in real-time on average hardware thanks to our improved dynamic programming based summary techniques. We performed several experiments using synthetic and real world surveillance videos, which showed the practical applicability of our system. Sample videos and their summaries can be reached at http://vision.gyte.edu.tr/projects.php?id=5.