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Paper TuD110.4

Rogers III, John G. (Georgia Institute of Technology), Christensen, Henrik Iskov (Georgia Institute of Technology)

A Conditional Random Field Model for Place and Object Classification

Scheduled for presentation during the Interactive Session "Interactive Session TuD-1" (TuD110), Tuesday, May 15, 2012, 16:30−17:00, Ballroom D

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on December 13, 2017

Keywords Domestic Robots, SLAM, Service Robots

Abstract

Place categorization and object recognition are competencies needed by robots to perform a variety of service tasks in the home, such as fetch-and-carry, retrieval, cleaning, meal preparation, and companionship. Context is a powerful cue for place categorization and object recognition; rooms are laid out in a specific fashion to enable comfortable and efficient living, and objects are used within rooms for tasks specific to that room. This paper will present a technique which leverages contextual cues for joint reasoning about object and room classification via a conditional random field model.

 

 

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