Recovering high dynamic range radiance maps from photographs
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Recovering photometric properties of architectural scenes from photographs
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
A practical analytic model for daylight
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
Color models for outdoor machine vision
Computer Vision and Image Understanding
All the Images of an Outdoor Scene
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
What is the Spectral Dimensionality of Illumination Functions in Outdoor Scenes?
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Direct HDR capture of the sun and sky
AFRIGRAPH '04 Proceedings of the 3rd international conference on Computer graphics, virtual reality, visualisation and interaction in Africa
Geometric Context from a Single Image
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
ACM SIGGRAPH 2006 Papers
Single-Image Vignetting Correction
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Clustering Appearance for Scene Analysis
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Learning Outdoor Color Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM SIGGRAPH 2007 papers
ACM SIGGRAPH 2007 papers
Robust Radiometric Calibration and Vignetting Correction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face swapping: automatically replacing faces in photographs
ACM SIGGRAPH 2008 papers
Priors for Large Photo Collections and What They Reveal about Cameras
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
What Does the Sky Tell Us about the Camera?
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Toward Fully Automatic Geo-Location and Geo-Orientation of Static Outdoor Cameras
WACV '08 Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision
Webcam clip art: appearance and illuminant transfer from time-lapse sequences
ACM SIGGRAPH Asia 2009 papers
Radiometric calibration from a single image
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Webcam clip art: appearance and illuminant transfer from time-lapse sequences
ACM SIGGRAPH Asia 2009 papers
Beyond GPS: determining the camera viewing direction of a geotagged image
Proceedings of the international conference on Multimedia
Estimating the Natural Illumination Conditions from a Single Outdoor Image
International Journal of Computer Vision
Removing shadows for color projection using sun position estimation
VAST'10 Proceedings of the 11th International conference on Virtual Reality, Archaeology and Cultural Heritage
Long-Range spatio-temporal modeling of video with application to fire detection
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Large scale visual geo-localization of images in mountainous terrain
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Object class detection: A survey
ACM Computing Surveys (CSUR)
Camera Spectral Sensitivity and White Balance Estimation from Sky Images
International Journal of Computer Vision
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As the main observed illuminant outdoors, the sky is a rich source of information about the scene. However, it is yet to be fully explored in computer vision because its appearance in an image depends on the sun position, weather conditions, photometric and geometric parameters of the camera, and the location of capture. In this paper, we analyze two sources of information available within the visible portion of the sky region: the sun position, and the sky appearance. By fitting a model of the predicted sun position to an image sequence, we show how to extract camera parameters such as the focal length, and the zenith and azimuth angles. Similarly, we show how we can extract the same parameters by fitting a physically-based sky model to the sky appearance. In short, the sun and the sky serve as geometric calibration targets, which can be used to annotate a large database of image sequences. We test our methods on a high-quality image sequence with known camera parameters, and obtain errors of less that 1% for the focal length, 1° for azimuth angle and 3° for zenith angle. We also use our methods to calibrate 22 real, low-quality webcam sequences scattered throughout the continental US, and show deviations below 4% for focal length, and 3° for the zenith and azimuth angles. Finally, we demonstrate that by combining the information available within the sun position and the sky appearance, we can also estimate the camera geolocation, as well as its geometric parameters. Our method achieves a mean localization error of 110 km on real, low-quality Internet webcams. The estimated viewing and illumination geometry of the scene can be useful for a variety of vision and graphics tasks such as relighting, appearance analysis and scene recovery.