由我校研究生院、党委研究生工作部主办，产业技术研究院、互联网医疗与健康服务河南省协同创新中心等联合承办的研究生“名师名家讲坛”，将邀请美国华盛顿大学Prof. Jenq-Neng Hwang做学术报告。欢迎广大师生积极参加！

报告题目：Coordinated Visual Mining of 3D Physical World for Smart City （智能城市三维物理世界的协调可视挖掘）

报 告 人：Prof. Jenq-Neng Hwang

报告时间：2018年9月14日（星期五） 上午10：00-12：00

报告地点：郑州大学南校区逸夫楼互联网医疗协同创新中心学术报告厅

报告人简介：

Prof. Jenq-Neng Hwang，博士，华盛顿大学（University of Washington）终身教授，IEEE Fellow。 分别于1981年和1983年获得台湾大学的电子工程专业学士和硕士学位，1989年获得美国南加利福尼亚大学（University of Southern California）电子工程博士学位，同年加入位于西雅图的华盛顿大学电子工程系，1999年至今为Full Professor，目前任电子工程系全球事务与国际发展副主席（Associate Chair）。发表期刊、会议、著作论文300余篇，Multimedia Signal Processing Technical Committee of IEEE Signal Processing Society发起人，MMTC、MMSP， IEEE Neural Network Council等会议的技术委员会成员，IEEE T-SP、T-NN、TCSVT、T-IP、SPM等期刊associate editor。

报告简介：

With the huge amount of networked video cameras available everywhere nowadays, such as the statically deployed surveillance cameras or the constantly moving cameras on the vehicles or drones, there is an urgent need of systematic and coordinated mining of the dynamic environment in the 3D physical world, so that the explored information can be exploited for various smart city applications, such as security surveillance, intelligent transportation, business statistics collection, health monitoring of communities, and etc. In this talk, I will first present an automated and robust human/vehicle tracking directly in 3D space through self-calibration of static and moving monocular cameras. These tracked objects locations and speed, as well as their poses, can all be described based on the GPS coordinates, so that the tracked objects from multiple cameras can then be easily exchanged, effectively integrated, as well as systematically reconstructed in the 3D real-world space for visualization and information sharing purposes.

研究生院

党委研究生工作部

产业技术研究院

互联网医疗与健康服务河南省协同创新中心

2018年9月10日