Assoc. Professor Jun Jo was awarded his PhD degree from the University of Sydney in 1994. For the PhD research, he studied Artificial Intelligence and Knowledge Representation techniques, and created an autonomous design system called EDGE. Dr Jo worked as a Postdoctoral Research Fellow at the Key Centre of Design Computing in the University of Sydney until he joined Griffith University in 1996. He has conducted many research projects in various areas including Computer Vision, Robotics, UAVs, Sensor Networks, Drones, eHealth and eLearning. He has published over 150 refereed publications.
Dr Jo has organised the International Robot Olympiad event twice in Australia, in 2006 and 2010. Dr Jo is currently taking the positions of the Chair of International Robot Olympiad Committee (IROC) and the President of Australian Robotics Association (ARA).
Dr Jo is also the Program Director for both Bachelor of Multimedia (BMM) and the Bachelor of Information Technology(BIT)/BMM double degree programs at Griffith University, Australia.
- 2016 – General co-chair, RiTA 2016: the 5th International Conference on Robot Intelligence Technology and Applications, Beijing, Dec 11-14, 2016.
- Since 2014 – Chair, Creative Technologies Challange (CTC), Australia
- Since 2009 – Chair, International Robot Olympiad Committee (IROC)
- Since 2008 – President, Australian Robotics Association
- Since 2003 – Director, Robotics and Computer Games (RnG) Lab
- 2010 – General Chair, the 12th International Robot Olympiad, Tellebudgera, Australia
- 2006 – General Chair, the 8th International Robot Olympiad, Southport, Australia
- Since 2004 – Editor, International Robot Olympiad News
- Since 2001 – Chair, Robot Soccer Simulation Committee, Federation for the Robot Soccer Association (FIRA)
- Since 2001 – Co-Editor, FIRA News
- 1997 – 2011 – Principal, Korean Language and Culture School, Southport, Gold Coast
- Postal Address – School of Information and Communication Technology, Griffith University, QLD Australia 4222
- Work Telephone – 61-07-5552 8266
- Fax – 61-07-5552 8066
- Email Address – firstname.lastname@example.org
Image Feature Detection, Description and Matching
The detection and description of image features help in object recognition. The collection of image features is very small in size and provides an efficient and accurate way for image matching.
Feature-based Object Matching
Workshop on Entrepreneurship, Seoul Korea, July
Multiple Face Recognition
Once a face has been registered in a database, CCTVs or drones can recognise the face at anytime at any place.
Face Detection and Chasing
The drone can detect and chase a target person.
Visits: Chairman of Korean National Assembly, Korean National Security Research Institute, Peking University, Hefei, Dr Woosuk Hwang
International Robot Olympiad 2015.
Scale In-variance Face Tracking
Smartphone-driven Autonomous Car
London Sky News
Smart UAV controlled by a Mobile phone
Mobile phone and Vision-based Driverless Car
Griffith University Robotics Group
Smartphone driven Robot Car