Indoor human face following with environmental fisheye cameras and blimp
A combination of fixed fisheye camera system and a blimp performed the task of human following in an indoor environment in this paper, focusing on tracking the subject's face. Hierarchical control algorithm is used to combine information from fisheye cameras and blimp's camera to track the...
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Published in | Advanced robotics Vol. 34; no. 9; pp. 621 - 636 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Taylor & Francis
02.05.2020
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Subjects | |
Online Access | Get full text |
ISSN | 0169-1864 1568-5535 |
DOI | 10.1080/01691864.2020.1747537 |
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Abstract | A combination of fixed fisheye camera system and a blimp performed the task of human following in an indoor environment in this paper, focusing on tracking the subject's face. Hierarchical control algorithm is used to combine information from fisheye cameras and blimp's camera to track the face to handle common human's translation and rotation movements. In this way, even when the face is not visible in the blimp's camera, the relative position between the blimp and the person is still available from fisheye cameras. The blimp can be controlled to move closer to the face, where it should be detectable. If the face can be detected and matched with the position of the person, the blimp can use it to adjust its position for a better track of the face. An experiment was conducted inside an office environment to demonstrate human following behavior of the blimp. With the face invisible to the blimp's camera 34.6 % of the experiment time, it could still move to recover the track of the face, using information from the fisheye cameras. |
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AbstractList | A combination of fixed fisheye camera system and a blimp performed the task of human following in an indoor environment in this paper, focusing on tracking the subject's face. Hierarchical control algorithm is used to combine information from fisheye cameras and blimp's camera to track the face to handle common human's translation and rotation movements. In this way, even when the face is not visible in the blimp's camera, the relative position between the blimp and the person is still available from fisheye cameras. The blimp can be controlled to move closer to the face, where it should be detectable. If the face can be detected and matched with the position of the person, the blimp can use it to adjust its position for a better track of the face. An experiment was conducted inside an office environment to demonstrate human following behavior of the blimp. With the face invisible to the blimp's camera 34.6 % of the experiment time, it could still move to recover the track of the face, using information from the fisheye cameras. |
Author | Ogata, Taiki Ota, Jun Yamashita, Atsushi Kuwahara, Noriaki Shirafuji, Shouhei Srisamosorn, Veerachart |
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Copyright | 2020 Informa UK Limited, trading as Taylor & Francis Group and The Robotics Society of Japan 2020 |
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SubjectTerms | aerial vehicle blimp Human detection and tracking sensor-based control vision-based control |
Title | Indoor human face following with environmental fisheye cameras and blimp |
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