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Detection and removal of lighting & shaking artifacts in home videos
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Source International Multimedia Conference archive
Proceedings of the tenth ACM international conference on Multimedia table of contents
Juan-les-Pins, France
SESSION: Session 4: video processing and transformation table of contents
Pages: 107 - 116  
Year of Publication: 2002
ISBN:1-58113-620-X
Authors
Wei-Qi Yan  National University of Singapore, Singapore
Mohan S Kankanhalli  National University of Singapore, Singapore
Sponsors
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
SIGCOMM: ACM Special Interest Group on Data Communication
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 11,   Downloads (12 Months): 91,   Citation Count: 11
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ABSTRACT

Many amateur videographers, like home video enthusiasts, may capture videos that are not of a professional quality. Many minor but visually annoying distortions like lighting imbalance and shaking artifacts could be introduced by the unskilled operations of the video camcorder. Since home videos constitute footage of great sentimental value, such videos cannot be summarily discarded. Unlike movies and sitcoms, shot re-takes of important events, such as wedding ceremonies are just not possible. Therefore, such distortions need to be corrected. In this paper, we present a novel method to detect segments of videos that have lighting and shaking artifacts. These segments can then be subjected to a restoration process that can remove these artifacts. We present techniques to correct lighting artifacts by appropriately adjusting the luminance. In order to remove the shaking artifact, image mosaicing is first employed to build a mosaic frame for the segment with the aid of edge blending techniques. Subsequently a Bezier-curve based blending of motion trajectory is employed to perform motion-compensated filtering of the shaking artifact. The restored video is then created by appropriately cropping the mosaic frame based on the compensated motion trajectory. We have implemented the developed techniques and the experimental results on home videos demonstrate the effectiveness of our approach. Detection and removal of artifacts are significant in other videos as well as those obtained from autonomous vehicles, robots and remote sensing.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  11

Collaborative Colleagues:
Wei-Qi Yan: colleagues
Mohan S Kankanhalli: colleagues