TY - GEN
T1 - Vision System with High Performance Wide Angle Fovea Lens
AU - Murakami, Rei
AU - Shimizu, Sota
AU - Hasebe, Nobuyuki
N1 - Funding Information:
ACKNOWLEDGMENT This study was partially supported by JSPS Grants-in-Aid for Scientific Research No.15K05914 and No.18K04055. The authors would like sincerely to appreciate Mr. Motonori Tominaga, Mr. Osamu Shimomura, Mr. Kazuhisa Ishimaru, SOKEN Inc. and Prof. Seiichi Mita, Toyota Institute of Technology, for their kind helps and supports. We also would like sincerely to thank all the members in Human Support Intelligent Robotics Laboratory, the other students and all the staffs in Department of Design and Engineering, Shibaura Institute of Technology.
PY - 2018/10/22
Y1 - 2018/10/22
N2 - This paper designs and produces a single camera head, i.e., the camera view direction control device, for the highperformance Wide Angle Fovea (WAF) sensor. Since the input image by the WAF sensor has an explicit attention region inside its wide-angle field of view (FOV), the view direction control of the WAF sensor is strongly required to acquire visual data most efficiently from the environments. Further, this paper proposes an algorithm to detect self-motion of the WAF sensor using the optical flow calculated from two temporally-sequential images. We have implemented and experimented this algorithm. The experimental results have proved the proposed algorithm performs well to detect self-motion using only the peripheral FOV. This vision system enables to distinguish the self-motion from detecting moving objects in the still scene. The authors hope this WAF vision system will play a role of eyes and will help to control robots more intelligently in the very near future.
AB - This paper designs and produces a single camera head, i.e., the camera view direction control device, for the highperformance Wide Angle Fovea (WAF) sensor. Since the input image by the WAF sensor has an explicit attention region inside its wide-angle field of view (FOV), the view direction control of the WAF sensor is strongly required to acquire visual data most efficiently from the environments. Further, this paper proposes an algorithm to detect self-motion of the WAF sensor using the optical flow calculated from two temporally-sequential images. We have implemented and experimented this algorithm. The experimental results have proved the proposed algorithm performs well to detect self-motion using only the peripheral FOV. This vision system enables to distinguish the self-motion from detecting moving objects in the still scene. The authors hope this WAF vision system will play a role of eyes and will help to control robots more intelligently in the very near future.
KW - optical flow
KW - self-motion detection
KW - single camera head
KW - view direction control
KW - wide angle fovea sensor
UR - http://www.scopus.com/inward/record.url?scp=85057289168&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85057289168&partnerID=8YFLogxK
U2 - 10.1109/ETFA.2018.8502661
DO - 10.1109/ETFA.2018.8502661
M3 - Conference contribution
AN - SCOPUS:85057289168
T3 - IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
SP - 1229
EP - 1232
BT - Proceedings - 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation, ETFA 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2018
Y2 - 4 September 2018 through 7 September 2018
ER -