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Proceedings Paper

Adaptive smoothing in real-time image stabilization
Author(s): Shunguang Wu; David C. Zhang; Yuzheng Zhang; James Basso; Michael Melle
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Paper Abstract

When using the conventional fixed smoothing factor to display the stabilized video, we have the issue of large undefined black border regions (BBR) when camera is fast panning and zooming. To minimize the size of BBR and also provide smooth visualization to the display, this paper discusses several novel methods that have demonstrated on a real-time platform. These methods include an IIR filter, a single Kalman filter and an interactive multi-model filter. The fundamentals of these methods are to adapt the smoothing factor to the motion change from time to time to ensure small BBR and least jitters. To further remove the residual BBR, the pixels inside the BBR are composited from the previous frames. To do that, we first store the previous images and their corresponding frame-to-frame (F2F) motions in a FIFO queue, and then start filling the black pixels from valid pixels in the nearest neighbor frame based on the F2F motion. If a matching is found, then the search is stopped and continues to the next pixel. If the search is exhausted, the pixel remains black. These algorithms have been implemented and tested in a TI DM6437 processor.

Paper Details

Date Published: 7 May 2012
PDF: 11 pages
Proc. SPIE 8399, Visual Information Processing XXI, 83990L (7 May 2012); doi: 10.1117/12.918737
Show Author Affiliations
Shunguang Wu, SRI International Sarnoff (United States)
David C. Zhang, SRI International Sarnoff (United States)
Yuzheng Zhang, SRI International Sarnoff (United States)
James Basso, SRI International Sarnoff (United States)
Michael Melle, SRI International Sarnoff (United States)


Published in SPIE Proceedings Vol. 8399:
Visual Information Processing XXI
Mark Allen Neifeld; Amit Ashok, Editor(s)

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