Feedback stitching for gigapixel video
Methods of stitching static panoramas are unsuitable for video-rate stitching from camera arrays, because these methods are too computationally intensive for real-time operation and do not take advantage of prior knowledge of camera positions or the coherence between successive frames of a video sequence. We propose feedback stitching, which embeds the stitching process in a feedback loop, so that as new frames are captured, any new stitching errors occurring in the video sequence are analyzed and corrected as the sequence progresses. These algorithms are suitable for multiscale cameras, a camera array technology proven to be capable of gigapixel snapshot and video imaging, to allow for real-time compensation of any registration or parallax errors.
Duke Scholars
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- Artificial Intelligence & Image Processing
- 4611 Machine learning
- 4607 Graphics, augmented reality and games
- 4603 Computer vision and multimedia computation
- 0801 Artificial Intelligence and Image Processing
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Related Subject Headings
- Artificial Intelligence & Image Processing
- 4611 Machine learning
- 4607 Graphics, augmented reality and games
- 4603 Computer vision and multimedia computation
- 0801 Artificial Intelligence and Image Processing