Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Model-Based Motion Estimation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Shape Indexing Using Approximate Nearest-Neighbour Search in High-Dimensional Spaces
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Automatic robust image registration system: Initialization, estimation, and decision
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
A Class of Algorithms for Fast Digital Image Registration
IEEE Transactions on Computers
Hybrid retinal image registration
IEEE Transactions on Information Technology in Biomedicine
Hi-index | 0.00 |
Short-term changes in atmospheric transmissivity caused by clouds can engender more severe fluctuations in photovoltaic (PV) outputs than those from traditional power plants. As PV energy continues to penetrate the U. S. National Energy Grid, such volatility increasingly lowers its reliability, efficiency, and value-added contribution. Therefore a model that can accurately predict the cloud motion and its affect on PV system's production is in a pressing demands. It can be used to mitigate the undesired behavior beforehand. In this paper we explore the use of Total Sky Images and the cloud estimation techniques based on such images. To further improve estimation quality of motion vector, we propose a novel hybrid algorithm taking the advantages of both correlation based and local feature based approaches. Our proposed hybrid approach significantly reduces the cloud motion prediction error rate by 25% on average, which can help to predict short term solar energy frustration in our later work.