Duke University

Francis McClernon

Romit Roy Choudhury

Lawrence L Carin

Matthew Engelhard

Jason Oliver

A system includes a camera configured to generate image data and a computing device in electronic communication with the camera. The computing device includes at least one processor and is configured to receive, from the camera, one or more images representative of a location. The computing device is further configured to apply a trained classifier to the one or more images to classify the location into one of at least two risk categories, wherein the classification is based on a likelihood of a subject performing a target behavior based on presence of the subject in the location. The computing device is additionally configured to issue a risk alert responsive to the trained classifier classifying the location into a high-risk category.

Systems and methods for predicting real-time behavioral risks using everyday images

Systems and methods for computing a geographic position of an object or event based on a geographic position of a computing device and a user gesture are disclosed herein. According to an aspect, a method includes determining a geographic position of a computing device. The method also includes receiving a user gesture on the computing device to indicate a direction towards a location from the computing device. Further, the method includes defining a geographic position of the location based on the geographic position of the computing device and the user gesture.

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Durham, NC, United States of America

Francis McClernon