We present a method that utilizes bracket sequence images to automatically extract the alpha matte of a motion-blurred object. This method makes use of a sharp, short-exposure snapshot in the sequence to help overcome major challenges in this task, including blurred object detection, spatially-variant object motion, and foreground/background color ambiguity. A key component of our matte estimation is the inference of approximate, spatially-varying motion of the blurred object with the help of the sharp snapshot, as this motion information provides important constraints on the aforementioned issues. In addition, we take advantage of other relationships that exist between a pair of consecutive short-exposure and long-exposure frames, such as common background areas and consistencies in foreground appearance. With this technique, we demonstrate successful alpha matting results on a variety of moving objects including non-rigid human motion. © 2014 Springer International Publishing.
CITATION STYLE
Myeong, H., Lin, S., & Lee, K. M. (2014). Alpha matting of motion-blurred objects in bracket sequence images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8691 LNCS, pp. 125–139). Springer Verlag. https://doi.org/10.1007/978-3-319-10578-9_9
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