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United States Patent	9,875,427
Barajas, et al.	July 12, 2016

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Method for Object Localization and Pose Estimation for an Object of Interest

Download: US Patent 9,875,427

[text]

AbstractA method for localizing and estimating a pose of a known object in a field of view of a vision system is described, and includes developing a processor-based model of the known object, capturing a bitmap image file including an image of the field of view including the known object, extracting features from the bitmap image file, matching the extracted features with features associated with the model of the known object, localizing an object in the bitmap image file based upon the extracted features, clustering the extracted features of the localized object, merging the clustered extracted features, detecting the known object in the field of view based upon a comparison of the merged clustered extracted features and the processor-based model of the known object, and estimating a pose of the detected known object in the field of view based upon the detecting of the known object.

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Inventors:	Medasani; Swarup (Thousand Oaks, CA), Meltzer; Jason (Los Angeles, CA), Xu; Jiejun (Chino, CA), Chen; Zhichao (Woodland Hills, CA), Sundareswara; Rashmi N. (Los Angeles, CA), Payton; David W. (Calabasas, CA), Uhlenbrock; Ryan M. (Los Angeles, CA), Barajas; Leandro G. (Harvest, AL), Kim; Kyungnam (Oak Park, CA)
Applicant:	Name City State Country Type GM GLOBAL TECHNOLOGY OPERATIONS LLC Detroit MI US
Assignee:	GM Global Technology Operations LLC (Detroit, MI)
Family ID:	1000003076227
Appl. No.:	14/811,062
Filed:	July 28, 2015

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A method for localizing and estimating a pose of a known object in a field of view of a vision system, the known object including a structural entity having pre-defined features including spatial dimensions, the method comprising: developing a processor-based model of the known object; capturing a bitmap image file including an image of the field of view including the known object; extracting features from the bitmap image file; matching the extracted features with features associated with the model of the known object; localizing an object in the bitmap image file based upon the extracted features, including identifying features in the bitmap image file associated with features of the known object, wherein identifying the features includes fitting a digital window around a region of interest in the bitmap image file and identifying features only in a portion of the bitmap image file within the digital window, and wherein fitting the digital window includes identifying inliers in the bitmap image file including data whose distribution can be explained by some set of model parameters associated with the known object; clustering the extracted features of the localized object; merging the clustered extracted features; detecting the known object in the field of view based upon a comparison of the merged clustered extracted features and the processor-based model of the known object; and estimating a pose of the detected known object in the field of view based upon the detecting of the known object.