Computer Graphics

University of California - Berkeley

User-Assisted Video Stabilization


We present a user-assisted video stabilization algorithm that is able to stabilize challenging videos when state-of-the-art automatic algorithms fail to generate a satisfactory result. Current methods do not give the user any control over the look of the final result. Users either have to accept the stabilized result as is, or discard it should the stabilization fail to generate a smooth output. Our system introduces two new modes of interaction that allow the user to improve the unsatisfactory stabilized video. First, we cluster tracks and visualize them on the warped video. The user ensures that appropriate tracks are selected by clicking on track clusters to include or exclude them. Second, the user can directly specify how regions in the output video should look by drawing quadrilaterals to select and deform parts of the frame. These user-provided deformations reduce undesirable distortions in the video. Our algorithm then computes a stabilized video using the user-selected tracks, while respecting the user-modified regions. The process of interactively removing user-identified artifacts can sometimes introduce new ones, though in most cases there is a net improvement. We demonstrate the effectiveness of our system with a variety of challenging hand held videos.


Jiamin Bai, Aseem Agarwala, Maneesh Agrawala, and Ravi Ramamoorthi. "User-Assisted Video Stabilization". Computer Graphics Forum (EGSR 2014), 2014.

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