A survey of image registration techniques
ACM Computing Surveys (CSUR)
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Registration of Video to Geo-Referenced Imagery
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Proceedings of the 2004 workshop on Multimedia and security
Gradient-based approach for fine registration of panorama images
Journal of Computer Science and Technology - Special issue on computer graphics and computer-aided design
Image-based spatio-temporal modeling and view interpolation of dynamic events
ACM Transactions on Graphics (TOG)
A survey of RST invariant image watermarking algorithms
ACM Computing Surveys (CSUR)
Automatic Panoramic Image Stitching using Invariant Features
International Journal of Computer Vision
Multi perspective panoramic imaging
Image and Vision Computing
Image stitching with dynamic elements
Image and Vision Computing
FSCAV: fast seam carving for size adaptation of videos
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Robust digital watermarking in videos based on geometric transformations
Proceedings of the international conference on Multimedia
Algorithms for video retargeting
Multimedia Tools and Applications
CamMark: a camcorder copy simulation as watermarking benchmark for digital video
Proceedings of the 5th ACM Multimedia Systems Conference
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Virtually every video watermarking technology can benefit from comparison with the original content. For non-blind schemes it is fundamental; for others it is an improvement to increase the watermark's signal-to-noise ratio by subtracting the content that is often noise to the detector. A direct frame-by-frame comparison of the videos is not possible due to the fact that illegal copies of videos usually differ significantly from their originals caused by different spatial resolution or frame rates, geometric distortions from capturing, or targeted attacks. In this paper, we present a software tool that enables the semi-automatic temporal and spatial synchronization of frames and pixels of two similar videos. This process is called registration. We put our focus on utilizing human capabilities with the smallest possible effort, to allow a high overall performance and precision of the registration. An efficient graphical user interface supports the users and visualizes the results of all steps. In addition, we specifically distinguish digitally reproduced copies from analog (camcorded) copies in which two or more frames are blended into a new frame.