Urc Ventures, Inc.

Everypoint, Inc.

The University of North Carolina at Chapel Hill

Jared Scott Heinly

David Bradley Boardman

Srinivas Kapaganty

Jan-Michael Frahm

Charles A Erignac

Brian Sanderson Clipp

Enrique Dunn

Johannes Lutz Schoenberger

Anthony James Jacobson

Peter S Barr

Daniel B Simon

Brooke N Steele

Techniques are described for automated analysis and use of data acquired about an object of interest, such as from a physically mounted camera or other sensing device with only partial coverage of the object exterior, such as to automatically generate a computer model of the object from visual data in images and to use the computer model to automatically estimate values for one or more object attributes. For example, the described techniques may be used to measure the volume of a pile of material significantly larger than a human using images acquired by one or more fixed-location cameras that provide visual coverage of only a subset of the pile's exterior. The images from such physically mounted devices may be acquired at various times (e.g., when triggered by conditions in the environment of the object, dynamically upon request, etc.), and may be used to monitor changes in the object.

Determining object structure using physically mounted devices with only partial view of object

Techniques are described for automated analysis and use of images acquired of an object and of associated image acquisition metadata, such as for manmade largescale objects at fixed locations in outdoor environments, and to automatically generate a 3D computer model of the object (e.g., the 3D shape of the object exterior's surface) from visual data in the acquired images and from image acquisition device motion data during the image acquisition, to use the computer model to automatically determine measurements for object attribute(s), and to display or otherwise provide information about the generated computer model and/or determined object attributes. The image acquisition metadata may include motion data from IMU (inertial measurement unit) sensors on the image acquisition device, and include additional related data that is determined based at least in part on that motion data (e.g., acquisition pose data for particular acquired images, 3D positions on object exterior, etc.).

Performing object modeling by combining visual data from images with motion data of the image acquisition device

Techniques are described for automated analysis and use of images acquired of an object of interest, such as from one or more fixed-location camera devices with only partial visual coverage of the object exterior, such as to automatically generate a computer model of the object from visual data in the images and to use the computer model to automatically estimate values for one or more object attributes. For example, the described techniques may be used to measure the volume of a pile of material significantly larger than a human using images acquired by one or more fixed-location cameras that provide visual coverage of only a subset of the pile's exterior. The images from such fixed-location cameras may be acquired at various times (e.g., when triggered by conditions in the environment of the object, dynamically upon request, etc.), and may be used to monitor changes in the object.

Determining object structure using fixed-location cameras with only partial view of object

Methods, systems, and computer readable media for image overlap detection. An example method includes identifying, by one or more computers, a collection of images; streaming, by the one or more computers, each image from the collection of images so that, in one or a limited number of passes through the collection of images, each image is loaded only once from an input source and each image is discarded after a processing time for the image is exceeded; and during the streaming, for each image in at least a first subset of the images in the collection, determining whether the image overlaps with at least one other image in the at least a first subset of the images.

Methods, systems, and computer readable media for image overlap detection

Techniques are described for analyzing images acquired via mobile devices in various ways, including to estimate measurements for one or more attributes of one or more objects in the images and/or to perform automated verification of such attribute measurements. For example, the described techniques may be used to measure the volume of a stockpile of material or other large object, based on images acquired via a mobile device that is moved around some or all of the object. The calculation of object volume and/or other determined object information may include generating and manipulating one or more computer models of the object from selected images. In addition, further automated verification activities may be performed for such computer model(s) and resulting object attribute measurements, such as based on analyzing one or more types of information that reflect accuracy and/or completeness of the computer model(s).

Verifying object measurements determined from mobile device images

Techniques are described for analyzing images acquired via mobile devices in various ways, including to estimate measurements for one or more attributes of one or more objects in the images, as well as determine changes over time in objects and their measurements based on images acquired at different times. For example, the described techniques may be used to measure the volume of a stockpile of material or other large object, based on images acquired via a mobile device that moves around some or all of the object. The calculation of object volume and/or other determined object information may include generating and manipulating one or more computer models of the object from selected images, and determining changes may include comparing different models for different times. In addition, further automated activities may include displaying, presenting or otherwise providing information about some or all of the determined information.

Growing community of inventors

Durham, NC, United States of America

Jared Scott Heinly