Prof. Reinhard Klette at Centre for Robotics & Vision at Auckland University of Technology, New Zealand
Towards Self-driving Cars: Test Fields, Visual Odometry, and Road-surface Analysis
Self-driving cars use various sensors, to be tested on extensive test fields under location, weather and traffic-specific conditions. The N3T vehicle test field is currently developing near Whangarei in New Zealand, in collaboration with the German Air- and Space Centre (DLR) and Auckland University of Technology (AUT).
In the context of test field studies, the talk informs about computer-vision based components towards self-driving cars. Visual odometry supports exact geo-localisation of vehicles on the road, and in particular also accurate 3-dimensional roadside reconstruction, thus improving GPS/IMU-only based approaches. The talk demonstrates reconstruction accuracy achieved in collaboration of DLR, AUT and N3T.
Different camera installations contribute to options for sensor configurations in self-driving cars. The talk discusses results for visual odometry for evaluating different camera “topologies”. It also demonstrates how visual odometry provides important information for improved road-surface distress analysis, such as automated pothole detection.
Prof. Reinhard Klette is the director of the Centre for Robotics & Vision at Auckland University of Technology, New Zealand. He is a Fellow of the Royal Society of New Zealand, received the Quancheng Friendship Award in China, and became a Helmholtz Fellow in Germany.
Professor Klette has been working in the area of computer vision for more than 30 years. In 2003 he published with the late Professor Azriel Rosenfeld of University of Maryland, USA, the first comprehensive monography on digital geometry (published by Morgan Kaufmann, San Francisco). He has become internationally renowned for his work in vision-based driver assistance since 2006, with important contributions on performance evaluation and improvements of correspondence algorithms on real-world video data, supporting, for example, 3D scene reconstruction from a mobile platform.
In 2008 he co-authored (with two of his former PhD students) a research monograph on panoramic vision (with Wiley, UK), in 2011 a research monograph (also co-authered with a former PhD student) on shortest paths in Euclidean spaces (with Springer, UK), and in 2017 a research monograph (also coauthered with a former PhD student) on vision-based driver assistance (with Springer, The Netherlands). His book entitled “Concise Computer Vision” has been published by Springer, London (UK) in 2014.
Since 1995, Professor Klette has been invited as a keynote or plenary speaker to international conferences worldwide. Between April 2011 and October 2013 he has been the founding Editor-in- Chief of the Journal of Control Engineering and Technology (JCET). He was an Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) between 2001 and 2008. He is a steering committee member of the biennial conferences on Computer Analysis of Images and Patterns, taking place in Europe, and a steering committee member of the Pacific-Rim Symposium on Image and Video Technology. He is the (local) General Chair of the Asian Conference on Pattern Recognition 2019.
Prof. Jiannong Cao at The Hong Kong Polytechnic University
Collaborative Task Execution in Advanced Edge Computing Environments
Advances in edge computing will boost more smart applications including AI models, AR, video analytics, and Industrial IoT applications. In an advanced edge computing environment, edge nodes of multiple stockholders are interconnected to facilitate the share of data and computation resources, and to collaborate on joint task execution using the shared resources. A fundamental issue is how to optimize the performance of collaborative task execution in terms of various metrics. In this talk, I will first introduce the major approaches to collaborative task execution, i.e., task partitioning, task allocation and task migration. In particular, I will present our recent work on multi-user multi-resource task partitioning, which is a new challenge and was not solved before. I will also highlight our works in data aware task allocation and task migration addressing the challenges arising from collaborative edge computing. Finally, I will conclude the talk by pointing out some future directions in this topic area.
Prof. Jiannong Cao is currently a Chair Professor of Department of Computing at The Hong Kong Polytechnic University, Hong Kong. He is also the director of the Internet and Mobile Computing Lab in the department and the director of University’s Research Facility in Big Data Analytics. His research interests include parallel and distributed computing, wireless sensing and networks, pervasive and mobile computing, and big data and cloud computing. He has co-authored 5 books, co-edited 9 books, and published over 600 papers in major international journals and conference proceedings. He received Best Paper Awards from conferences including, IEEE Trans. Industrial Informatics 2018, IEEE DSAA 2017, IEEE SMARTCOMP 2016, IEEE/IFIP EUC 2016, IEEE ISPA 2013, IEEE WCNC 2011, etc. Dr. Cao has directed and participated in over 90 research and development projects and, as a principal investigator, obtained over HK$43 million grants
Dr. Cao is currently a Chair Professor of Department of Computing at The Hong Kong Polytechnic University, Hong Kong. He is also the director of the Internet and Mobile Computing Lab in the department and the director of University’s Research Facility in Big Data Analytics. He served the department head from 2011 to 2017.
Dr. Cao’s research interests include parallel and distributed computing, wireless sensing and networks, pervasive and mobile computing, and big data and cloud computing. He has directed and participated in over 90 research and development projects and, as a principal investigator, obtained over HK$60 million grants from various funding agencies. He published 5 co-authored and 9 co-edited books, and over 500 papers in major international journals and conference proceedings. Dr. Cao also received Best Paper Awards from journals and conferences including IEEE TII, DSAA’2017, SMARTCOMP 2016, ISPA 2013, and IEEE WCNC 2011.
Dr. Cao served the Chair of the Technical Committee on Distributed Computing of IEEE Computer Society 2012-2014, and a member of many IEEE and other professional committees. He has served as chairs and members of organizing and technical committees of many international conferences, and as editors of many international journals. Dr. Cao is a fellow of IEEE and ACM distinguished member. In 2017, he received the Overseas Outstanding Contribution Award from China Computer Federation.