A multiresolution spline with application to image mosaics
ACM Transactions on Graphics (TOG)
Interactive Construction of 3D Models from Panoramic Mosaics
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Graphcut textures: image and video synthesis using graph cuts
ACM SIGGRAPH 2003 Papers
ACM SIGGRAPH 2003 Papers
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Interactive digital photomontage
ACM SIGGRAPH 2004 Papers
A Riemannian Framework for Tensor Computing
International Journal of Computer Vision
ACM SIGGRAPH 2006 Papers
Streaming multigrid for gradient-domain operations on large images
ACM SIGGRAPH 2008 papers
Image segmentation based on GrabCut framework integrating multiscale nonlinear structure tensor
IEEE Transactions on Image Processing
Fast Image Labeling for Creating High-Resolution Panoramic Images on Mobile Devices
ISM '09 Proceedings of the 2009 11th IEEE International Symposium on Multimedia
A 2-point algorithm for 3D reconstruction of horizontal lines from a single omni-directional image
Pattern Recognition Letters
A robust template tracking algorithm with weighted active drift correction
Pattern Recognition Letters
Joint photometric and geometric image registration in the total least square sense
Pattern Recognition Letters
B-spline signal processing. II. Efficiency design and applications
IEEE Transactions on Signal Processing
Panorama Mosaic Optimization for Mobile Camera Systems
IEEE Transactions on Consumer Electronics
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Optimal seam finding is a popular panorama construction strategy. It has the advantage of constructing panorama rapidly as well as being memory efficient. However, it is intrinsically sensitive to radiometric distortions, which is why artifacts are often visible in the composed panorama. Besides, it requires users to specify weight parameters, making such algorithms difficult to configure. In this paper, by fully exploiting the camera model and utilizing the knowledge of tensor analysis, we propose a novel optimal seam finding method. It not only enables the creation of artifact-free panorama from distorted input images but also requires no user-specified weights. We verify the effectiveness of our method by testing it on variegated sets of images with different types of optical distortions.