Image Alignment and Stitching: A Tutorial (Foundations and Trends(r) in Computer Graphics and Vision)

Image Alignment and Stitching: A Tutorial reviews image alignment and image stitching algorithms. Image alignment algorithms can discover the correspondence relationships among images with varying degrees of overlap. They are ideally suited for applications such as video stabilization, summarization, and the creation of panoramic mosaics. Image stitching algorithms take the alignment estimates produced by such registration algorithms and blend the images in a seamless manner, taking care to deal with potential problems such as blurring or ghosting caused by parallax and scene movement as well as varying image exposures. Image Alignment and Stitching: A Tutorial reviews the basic motion models underlying alignment and stitching algorithms, describes effective direct (pixel-based) and feature-based alignment algorithms, and describes blending algorithms used to produce seamless mosaics. It closes with a discussion of open research problems in the area. Image Alignment and Stitching: A Tutorial is an invaluable resource for anyone planning or conducting research in this particular area, or computer vision generally. The essentials of the topic are presented in a tutorial style and an extensive bibliography guides towards further reading. This tutorial reviews image alignment and image stitching algorithms. Image alignment algorithms can discover the correspondence relationships among images with varying degrees of overlap. They are ideally suited for applications such as video stabilization, summarization, and the creation of panoramic mosaics. Image stitching algorithms take the alignment estimates produced by such registration algorithms and blend the images in a seamless manner, taking care to deal with potential problems such as blurring or ghosting caused by parallax and scene movement as well as varying image exposures. This tutorial reviews the basic motion models underlying alignment and stitching algorithms, describes effective direct (pixel-based) and feature-based alignment algorithms, and describes blending algorithms used to produce seamless mosaics. It ends with a discussion of open research problems in the area Introduction......Page 12 Motion Models......Page 16 2D (planar) Motions......Page 17 3D Transformations......Page 19 Cylindrical and Spherical Coordinates......Page 26 Lens Distortions......Page 29 Direct (pixel-based) Alignment......Page 32 Error Metrics......Page 33 Hierarchical Motion Estimation......Page 36 Fourier-Based Alignment......Page 38 Incremental Refinement......Page 42 Parametric Motion......Page 48 Keypoint Detectors......Page 54 Feature Matching......Page 58 Geometric Registration......Page 63 Direct vs. Feature-Based Alignment......Page 70 Bundle Adjustment......Page 74 Parallax Removal......Page 79 Recognizing Panoramas......Page 81 Choosing a Compositing Surface......Page 86 Pixel Selection and Weighting......Page 89 Blending......Page 95 Extensions and Open Issues......Page 102 References......Page 106 'Originally published as Foundations and trends in computer graphics and vision, volume 2, issue 1 (2006)'--P. [4] of cover.