2016/08/29 by William X. Liu, Tat-Jun Chin, Liu, William X. +1
Computer Science · Engineering · #Advanced Image and Video Retrieval Techniques #Advanced Vision and Imaging #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Robotics and Sensor-Based Localization #cs.CV
paper · pdf · doi:10.48550/arxiv.1608.07997
arxiv created 2016/08/29 · openalex publication_date 2016/08/29 · arxiv updated 2016/08/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Spatially varying warps are increasingly popular for image alignment. In particular, as-projective-as-possible (APAP) warps have been proven effective for accurate panoramic stitching, especially in cases with significant depth parallax that defeat standard homographic warps. However, estimating spatially varying warps requires a sufficient number of feature matches. In image regions where feature detection or matching fail, the warp loses guidance and is unable to accurately model the true underlying warp, thus resulting in poor registration. In this paper, we propose a correspondence insertion method for APAP warps, with a focus on panoramic stitching. Our method automatically identifies misaligned regions, and inserts appropriate point correspondences to increase the flexibility of the warp and improve alignment. Unlike other warp varieties, the underlying projective regularization of APAP warps reduces overfitting and geometric distortion, despite increases to the warp complexity. Comparisons with recent techniques for parallax-tolerant image stitching demonstrate the effectiveness and simplicity of our approach.