Wide Baseline Image Mosaicing by Integrating MSER and Hessian-Affine
In this paper we propose a novel approach for widebaseline image mosaicing which integrates MSER and Hessian-Affine detectors. MSER and Hessian-Affine are both robust detectors for wide-baseline stereo matching and they can be integrated owing to their availability in the structured scenes and the richtextured scenes separately. However, the output shape of them is different, so they cannot be directly integrated. We use an affine covariant construction method to unify their output shape. At the same time, we introduce a standard elliptic equation to unify the ellipse parameters. The axial length and rotation matrix of ellipse with scale are calculated in accordance to the eigenvalue and eigenvector of image feature regions. Then MSER and Hessian-Affine regions are constructed as standard elliptical regions, and described as a unified parameter form. Our method provides more plentiful and robust features so that wide-baseline images can be stitched well. We design an experiment to compare the proposed method with the method based on SIFT. By testing 30 various image pairs, our experiment indicates that the proposed method is effective and available for the wide baseline images mosaicing, especially in the structured scenes with rich texture.
image mosaicing MSER Hessian-Affine wide baseline
Yufang Ning Ren Chen Pengfei Xu
School of Computer Engineering and Science, Shanghai University Shanghai, China
国际会议
2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)
上海
英文
2067-2070
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）