A multiresolution spline with application to image mosaics
ACM Transactions on Graphics (TOG)
Creating full view panoramic image mosaics and environment maps
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Robust Video Mosaicing through Topology Inference and Local to Global Alignment
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Panoramic mosaics by manifold projection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
VideoBrushTM: Experiences with Consumer Video Mosaicing
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Efficiently Registering Video into Panoramic Mosaics
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Automatic Panoramic Image Stitching using Invariant Features
International Journal of Computer Vision
Image alignment and stitching: a tutorial
Foundations and Trends® in Computer Graphics and Vision
Video Mosaics for Virtual Environments
IEEE Computer Graphics and Applications
Fast construction of dynamic and multi-resolution 360° panoramas from video sequences
Image and Vision Computing
Robust digital image stabilization using the Kalman filter
IEEE Transactions on Consumer Electronics
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A video sequence consists of several hundred frames and as a result creating a panoramic image from these frames is a very time consuming process. Consecutive frames have large overlap areas which do not provide much information. Therefore, some key frames must be extracted for better performance. There are a number of methods for key frame selection, which match all frames in a video sequence. In this paper, we present a novel and efficient method to select key frames from video for creating a large panoramic mosaic without matching all frames. A Kalman filter is used to predict the overlap area between each frame and its previous key frame. It predicts the trajectory of each frame corner to estimate its position in a common mosaic surface. It is shown that this approach substantially reduces the time required to construct panorama from a video sequence.