Robust regression and outlier detection
Robust regression and outlier detection
Robust regression methods for computer vision: a review
International Journal of Computer Vision
Introductory Techniques for 3-D Computer Vision
Introductory Techniques for 3-D Computer Vision
Optical flow techniques applied to video coding
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
Towards Teleconferencing by View Synthesis and Large-Baseline Stereo
ICIAP '01 Proceedings of the 11th International Conference on Image Analysis and Processing
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
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In this paper we present some preliminary results on an optical-flow based technique aimed at recovering the cloud-top height from infra-red image sequences. This work has been carried out in the context of the development of the "Extreme Universe Space Observatory" mission (EUSO), an ESA led international mission for the investigation of the nature and origin of Extreme Energy Cosmic Rays. The knowledge of the cloud scenario is critical to measure the primary energy and the composition of EECRs. In this work we explore the feasibility for the cloud-top height recovery, of a technique based on a robust multi-resolution optical-flow algorithm. The robustness is achieved adopting a Least Median of Squares paradigm. The algorithm has been tested on semi-synthetic data (i.e. real data that have been synthetically warped in order to have a reliable ground truth for the motion field), and on real short sequences (pairs of frames) coming from the ATSR2 data set. Since we assumed the same geometry as for the ATSR2 data, the cloud top height could be recovered from the motion field by means of the widely used Prata and Turner equation.