Xin Chen Gives ACM SIGSPATIAL Keynote
He is working to achieve the automation of next generation map creation using computer vision and machine learning technologies.
Prof. Xin Chen delivered an Invited Keynote Talk at 26th ACM SIGSPATIAL GIS conference, titled, "HD Live Maps for Automated Driving: An AI Approach" on November 7 in Seattle, WA.
Talk Abstract: HD Maps, one of the key components of automated driving and a life-saving safety feature, serve as the hub for sensing, perception and decision. Making and maintaining a near-real time HD map on a global scale is an extremely challenging task. I will present how we apply AI technologies to automate the creation of HD Live Maps using both industrial capture and crowd- sourced based data collection. Quality Index is introduced to provide automated driving customers with the confidence of HD map accuracy and reliability in a dynamic world. We implement low power and high throughput edge perception as a reference implementation to enable crowd-sourced based HD map maintenance. Finally I will share best practices to democratize AI in our engineering organization and transition research into production in the creation of a half million kilometers of HD maps in 2017.
The ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2018 (ACM SIGSPATIAL 2018) is the twenty sixth event in a series of symposia and workshops that began in 1993 with the aim of bringing together researchers, developers, users, and practitioners in relation to novel systems based on geo-spatial data and knowledge, and fostering interdisciplinary discussions and research in all aspects of geographic information systems. The conference provides a forum for original research contributions covering all conceptual, design, and implementation aspects of geospatial data ranging from applications, user interfaces, and visualization to data storage and query processing and indexing. The conference is the premier annual event of the ACM Special Interest Group on Spatial Information (ACM SIGSPATIAL).