报告内容：Our Approaches Toward Winning All Tracks of 2019 CVF/IEEE CVPR AI City Challenge
报告人：Prof. Jenq-Neng Hwang
报告时间：12月9日 9:30
报告地点：现代交通工程中心7950会议室
报告人简介:
Dr. Jenq-Neng Hwang received the BS and MS degrees, both in electrical engineering from the National Taiwan University, Taipei, Taiwan, in 1981 and 1983 separately. He then received his Ph.D. degree from the University of Southern California. In the summer of 1989, Dr. Hwang joined the Department of Electrical and Computer Engineering (ECE) of the University of Washington in Seattle, where he has been promoted to Full Professor since 1999. He served as the Associate Chair for Research from 2003 to 2005, and from 2011-2015. He is currently the Associate Chair for Global Affairs and International Development in the ECE Department. He is the founder and co-director of the Information Processing Lab., which has won CVPR AI City Challenges awards consecutively in the past years. He has written more than 350 journal, conference papers and book chapters in the areas of machine learning, multimedia signal processing, and multimedia system integration and networking, including an authored textbook on Multimedia Networking: from Theory to Practice, published by Cambridge University Press. Dr. Hwang has close working relationship with the industry on multimedia signal processing and multimedia networking.
Dr. Hwang received the 1995 IEEE Signal Processing Society's Best Journal Paper Award. He is a founding member of Multimedia Signal Processing Technical Committee of IEEE Signal Processing Society and was the Society's representative to IEEE Neural Network Council from 1996 to 2000. He is currently a member of Multimedia Technical Committee (MMTC) of IEEE Communication Society and also a member of Multimedia Signal Processing Technical Committee (MMSP TC) of IEEE Signal Processing Society. He served as associate editors for IEEE T-SP, T-NN and T-CSVT, T-IP and Signal Processing Magazine (SPM). He is currently on the editorial board of ZTE Communications, ETRI, IJDMB and JSPS journals. He served as the Program Co-Chair of IEEE ICME 2016 and was the Program Co-Chairs of ICASSP 1998 and ISCAS 2009. Dr. Hwang is a fellow of IEEE since 2001.
报告内容简介:
With millions of traffic video cameras acting as sensors around the world, there is a significant opportunity for real-time and batch analysis of these videos to provide actionable insights. These insights will benefit a wide variety of agencies, from traffic control to public safety. The 2019 AI City Challenge is the third annual edition in the AI City Challenge series with significant growing attention and participation. AI City Challenge 2019 enabled 334 academic and industrial research teams from 44 countries to solve real-world problems using real city-scale traffic camera video data. The Challenge was launched with three tracks. Track 1 addressed city-scale multi-camera vehicle tracking, Track 2 addressed city-scale vehicle re-identification, and Track 3 addressed traffic anomaly detection. Each track was chosen in consultation with departments of transportation focusing on problems of greatest public value. As a top-ranking team, I would like to share our approaches toward solving all three tracks of challenge in this talk.
