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dc.contributor.advisorYun, Xiaoping
dc.contributor.advisorCalusdian, James
dc.contributor.authorGreenberg, Rebecca A.
dc.dateJun-17
dc.date.accessioned2017-08-14T16:48:09Z
dc.date.available2017-08-14T16:48:09Z
dc.date.issued2017-06
dc.identifier.urihttp://hdl.handle.net/10945/55606
dc.descriptionApproved for public release; distribution is unlimiteden_US
dc.description.abstractHuman detection, tracking, and following is one application in which computer vision can be relevant to robotics. By using a sequence of images, a human can be found and that human's movement can be followed. The Microsoft Kinect, one of the most successful color image and depth (RGB-D) sensors, is known for its human detection capabilities and has multiple software development kits available. The objective of this thesis was to determine if it was feasible to implement human tracking and following on a mobile robot in an indoor environment. Specifically, the tracking was conducted with the Microsoft Kinect and a specific software development environment, Robot Operating System (ROS) and MATLAB. ROS was utilized to run the drivers for the robot and the Microsoft Kinect, while MATLAB was utilized to run the algorithms and experiments. The skeleton tracking capabilities of the Kinect were utilized as the main tracking system. An auxiliary method was created by using histograms of depth and region properties to segment a person from a depth image. The indoor robot was able to successfully track and follow a person through the indoor environment using the raw sensor data and a combination of the two tracking methods.en_US
dc.description.urihttp://archive.org/details/investigatingfea1094555606
dc.publisherMonterey, California: Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleInvestigating the feasibility of conducting human tracking and following in an indoor environment using a Microsoft Kinect and the Robot Operating Systemen_US
dc.typeThesisen_US
dc.contributor.departmentElectrical and Computer Engineering (ECE)
dc.subject.authorroboten_US
dc.subject.authorRobot Operating Systemen_US
dc.subject.authorKinecten_US
dc.subject.authorP3-DXen_US
dc.subject.authorhuman detectionen_US
dc.subject.authorhuman tracking and followingen_US
dc.description.serviceEnsign, United States Navyen_US
etd.thesisdegree.nameMaster of Science in Electrical Engineeringen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineElectrical Engineeringen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


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