<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Caroline Pantofaru</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">User Observation &amp; Dataset Collection for Robot Training</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. of Human-Robot Interaction (HRI)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">computer vision</style></keyword><keyword><style  face="normal" font="default" size="100%">HRI</style></keyword><keyword><style  face="normal" font="default" size="100%">perception</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2011</style></date></pub-dates></dates><urls><related-urls><url><style face="normal" font="default" size="100%">http://www.willowgarage.com/sites/default/files/lbr251-pantofaru.pdf</style></url></related-urls></urls><publisher><style face="normal" font="default" size="100%">ACM Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Lausanne, CH</style></pub-location><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Personal robots operate in human environments such as homes and offices, co-habiting with people. To effectively train robot algorithms for such scenarios, a large amount of training data containing both people and the environment is required. Collecting such data involves taking a robot into new environments,  observing and interacting with people. So far, best practices for robot data collection have been undefined. Fortunately, the human-robot interaction community has conducted field studies whose methodology can serve as a model. In this paper, we draw parallels between field study observation and the data collection process, suggesting that best practices may be transferable. As a use case, we present a robot sensor dataset for training and testing algorithms for person detection in indoor environments.&lt;/p&gt;</style></abstract></record></records></xml>
