Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Artificial Intelligence - Special volume on computer vision
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-Calibration of a Moving Camera from PointCorrespondences and Fundamental Matrices
International Journal of Computer Vision
Using geometric corners to build a 2D mosaic from a set of image
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Construction and Refinement of Panoramic Mosaics with Global and Local Alignment
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Comparing and Evaluating Interest Points
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Video Mosaics for Virtual Environments
IEEE Computer Graphics and Applications
Colour indexing across illumination
IM'99 Proceedings of the 1999 international conference on Challenge of Image Retrieval
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International Journal of Geographical Information Science
Compression and distribution of panoramic videos utilising MPEG-7-based image registration
Multimedia Tools and Applications
Image Based Quantitative Mosaic Evaluation with Artificial Video
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
LLE based gait analysis and recognition
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
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This paper begins by reviewing the current state-of-the-art for imaging mosaic and applications. Then a new approach that uses a four-step automatic imaging mosaic, based on interest points, is proposed. The four steps are identification of interest points, finding corresponding points in the stitching images, deriving the spatial and spectral transform matrix then image mosaic and smoothing. The advantage of this approach is that it is robust to image capture conditions such as lighting, rotation, viewpoint and capture device.