Vision-based Reacquisition for Task-level Control Matthew R. Walter, Yuli Friedman, Matthew Antone, and Seth Teller Abstract We describe a vision-based algorithm that enables a robot to “reacquire” objects previously - Vision Objects - Document - PDFSEARCH.IO

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	Vision-based Reacquisition for Task-level Control Matthew R. Walter, Yuli Friedman, Matthew Antone, and Seth Teller Abstract We describe a vision-based algorithm that enables a robot to “reacquire” objects previously Add to Reading List Document Date: 2014-11-19 14:27:01 Open Document File Size: 3,73 MB Share Result on Facebook / IndustryTerm video stream onboard wireless / normalized inner product / reacquisition algorithm / object reacquisition algorithm / / Organization Teller MIT CS & AI Lab / / Person Yuli Friedman / Matthew R. Walter / Matthew Antone / Mi / Seth Teller / / Position visual appearance model for each user- / model / teller / human supervisor / particular object model / / Product The tablet / / ProgrammingLanguage FP / / Technology Lowe’s SIFT algorithm / vision-based algorithm / object reacquisition algorithm / artificial intelligence / reacquisition algorithm / Object Reacquisition Our algorithm / / SocialTag Object recognition Pose Video tracking Robotics Segmentation Robot Scale-invariant feature transform 3D single object recognition Computer vision Vision

Vision-based Reacquisition for Task-level Control Matthew R. Walter, Yuli Friedman, Matthew Antone, and Seth Teller Abstract We describe a vision-based algorithm that enables a robot to “reacquire” objects previouslyAdd to Reading List