Regional foremost matching for internet scene images
Refereed conference paper presented and published in conference proceedings

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AbstractWe analyze the dense matching problem for Internet scene images based on the fact that commonly only part of images can be matched due to the variation of view angle, motion, objects, etc. We thus propose regional foremost matching to reject outlier matching points while still producing dense high-quality correspondence in the remaining foremost regions. Our system initializes sparse correspondence, propagates matching with model fitting and optimization, and detects foremost regions robustly. We apply our method to several applications, including time-lapse sequence generation, Internet photo composition, automatic image morphing, and automatic rephotography.
All Author(s) ListXiaoyong Shen, Xin Tao, Chao Zhou, Hongyun Gao, Jiaya Jia
Name of ConferenceACM SIGGRAPH Asia 2016
Start Date of Conference05/12/2016
End Date of Conference09/12/2016
Place of ConferenceMacao
Country/Region of ConferenceChina
Proceedings TitleACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2016
Volume Number35
Issue Number6
LanguagesEnglish-United States

Last updated on 2022-13-01 at 00:50