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Content Provider | IEEE Xplore Digital Library |
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Author | Kirchner, N. Alempijevic, A. Virgona, A. |
Copyright Year | 2012 |
Description | Author affiliation: Centre for Autonomous Systems University of Technology Sydney, Australia (Kirchner, N.; Alempijevic, A.; Virgona, A.) |
Abstract | Ensuring that an interaction is initiated with a particular and unsuspecting member of a group is a complex task. As a first step the robot must effectively, expediently and reliably recognise the humans as they carry on with their typical behaviours (in situ). A method for constructing a scale and viewing angle robust feature vector (from analysing a 3D pointcloud) designed to encapsulate the inter-person variations in the size and shape of the people's head to shoulder region (Head-to-shoulder signature - HSS) is presented. Furthermore, a method for utilising said feature vector as the basis of person recognition via a Support-Vector Machine is detailed. An empirical study was performed in which person recognition was attempted on in situ data collected from 25 participants over 5 days in a office environment. The results report a mean accuracy over the 5 days of 78.15% and a peak accuracy 100% for 9 participants. Further, the results show a considerably better-than-random (1/23 = 4.5%) result for when the participants were: in motion and unaware they were being scanned (52.11%), in motion and face directly away from the sensor (36.04%), and post variations in their general appearance. Finally, the results show the HSS has considerable ability to accommodate for a person's head, shoulder and body rotation relative to the sensor - even in cases where the person is faced directly away from the robot. |
Starting Page | 1226 |
Ending Page | 1231 |
File Size | 1320779 |
Page Count | 6 |
File Format | |
ISBN | 9781467314039 |
ISSN | 10504729 |
e-ISBN | 9781467314053 |
e-ISBN | 9781467314046 |
DOI | 10.1109/ICRA.2012.6224901 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-05-14 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Robot sensing systems Accuracy Robustness Humans Training data Legged locomotion |
Content Type | Text |
Resource Type | Article |
Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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