Comprehensive interest points based imaging mosaic
Pattern Recognition Letters
Image Registration with Global and Local Luminance Alignment
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Objective Image Fusion Performance Characterisation
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
An image mosaicing module for wide-area surveillance
Proceedings of the third ACM international workshop on Video surveillance & sensor networks
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
Interest towards image mosaicing has existed since the dawn of photography. Many automatic digital mosaicing methods have been developed, but unfortunately their evaluation has been only qualitative. Lack of generally approved measures and standard test data sets impedes comparison of the works by different research groups. For scientific evaluation, mosaic quality should be quantitatively measured, and standard protocols established. In this paper the authors propose a method for creating artificial video images with virtual camera parameters and properties for testing mosaicing performance. Important evaluation issues are addressed, especially mosaic coverage. The authors present a measuring method for evaluating mosaicing performance of different algorithms, and showcase it with the root-mean-squared error. Three artificial test videos are presented, ran through real-time mosaicing method as an example, and published in the Web to facilitate future performance comparisons.