Connor Greenwell

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Estimating the focal length of an image is an important preprocessing step for many applications. Despite this, existing methods for single-view focal length estimation are limited in that they require particular geometric calibration objects, such as orthogonal vanishing points, co-planar circles, or a calibration grid, to occur in the field of view. In(More)
We propose the use of deep convolutional neural networks to estimate the transient attributes of a scene from a single image. Transient scene attributes describe both the objective conditions, such as the weather, time of day, and the season, and subjective properties of a scene, such as whether or not the scene seems busy. Recently, convolutional neural(More)
The images uploaded to social networking websites are a rich source of information about the appearance of people around the world. We present a system, GeoFaceExplorer, for collecting, processing, browsing, and analyzing this data. GeoFaceExplorer allows for the crowdsourced collection of human facial images, as well as automated and interactive visual(More)
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