Regional foremost matching for internet scene images
Xiaoyong Shen, Xin Tao, Chao Zhou, Hongyun Gao, Jiaya Jia · ACM Transactions on Graphics · 2016
We 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 proposeregional foremost matchingto 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.