Abstract
Non-Photorealistic Rendering (NPR) can offer increased concentration and familiarity to the watcher. For this reason, many media such as movies, games, and commercials currently use the NPR method to deliver information. In this paper, we suggest an interactive system for video cartooning based on the mean-shift segmentation of image and video. In order to solve the problems of time complexity and memory allocation, the conventional problems of video mean-shift segmentation, this paper proposes several techniques such as foreground object based segmentation and sequential segmentation. We also propose the interactive correction technique to get enhanced results. For more cartoonic representation, we used spline curve approximation of segment boundaries in the final rendering results. With our method, we can easily create cartoon rendering output using the video streams such like home video, which can be obtained easily in our daily life.
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Hong, SS., Yoon, JC., Lee, IK., Byun, S. (2007). Interactive System for Efficient Video Cartooning. In: Gagalowicz, A., Philips, W. (eds) Computer Vision/Computer Graphics Collaboration Techniques. MIRAGE 2007. Lecture Notes in Computer Science, vol 4418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71457-6_15
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DOI: https://doi.org/10.1007/978-3-540-71457-6_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71456-9
Online ISBN: 978-3-540-71457-6
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