ECE Seminar* Speaker: Dr. Yung-Hsiang Lu, Associate Professor, School of Electrical and Computer Engineering, Purdue University
When: Monday,
May 9, 2016
2:00 PM
-
3:00 PM
Where: Science & Engineering Building, Lester W. Cory Conference Room: Room 213A
Cost: Free
Description: Topic: Opportunities and Challenges of Global Network Cameras
Location: Lester W. Cory Conference Room, Science & Engineering Building (Group II), Room 213A
Abstract:
Millions of network cameras have been deployed. Many of these cameras provide publicly available data, continuously streaming live views of national parks, city halls, streets, highways, and shopping malls. A person may see multiple tourist attractions through these cameras, without leaving home. Researchers may observe the weather in different cities. Using the data, it is possible to observe natural disasters at a safe distance. News reporters may obtain instant views of an unfolding event. A spectator may watch a celebration parade from multiple locations using street cameras. Despite the many promising applications, the opportunities of using global network cameras for creating multimedia content have not been fully exploited. The opportunities also bring forth many challenges. Managing the large amount of data would require fundamentally new thinking. The data from network cameras are unstructured and have few metadata describing the content. Searching the relevant content would be a challenge. Because network cameras continuously produce data, processing must be able to handle the streaming data. This imposes stringent requirements of the performance. In this presentation, I will share the experience building a software system that aims to explore the opportunities using the data from global network cameras. CAM2 (Continuous Analysis of Many CAMeras, https://cam2.ecn.purdue.edu/) is cloud-based system for studying the worldwide phenomena using network cameras. CAM2 provides an event-based API (application programming interface) and is open to researchers to analyze the data for their studies. The web interface allows users to select the cameras for analysis. The cloud computing engine can scale in response to the needs of analysis programs.
Biography:
Yung-Hsiang Lu is an associate professor in the School of Electrical and Computer Engineering of Purdue University. He is an ACM distinguished scientist and ACM distinguished speaker. He is the lead investigator of a software system for analyzing thousands of network cameras worldwide. This cloud-based system can retrieve and analyze real-time visual data. More than 200 people have signed up as users. He is the lead organizer of the first Low-Power Image Recognition Challenge in 2015. He obtained the Ph.D. from Stanford University.
This Seminar is open to the public free of charge.
*For further information, please contact Dr. Honggang Wang at 508.999.8469, or via email at hwang1@umassd.edu.
Location: Lester W. Cory Conference Room, Science & Engineering Building (Group II), Room 213A
Abstract:
Millions of network cameras have been deployed. Many of these cameras provide publicly available data, continuously streaming live views of national parks, city halls, streets, highways, and shopping malls. A person may see multiple tourist attractions through these cameras, without leaving home. Researchers may observe the weather in different cities. Using the data, it is possible to observe natural disasters at a safe distance. News reporters may obtain instant views of an unfolding event. A spectator may watch a celebration parade from multiple locations using street cameras. Despite the many promising applications, the opportunities of using global network cameras for creating multimedia content have not been fully exploited. The opportunities also bring forth many challenges. Managing the large amount of data would require fundamentally new thinking. The data from network cameras are unstructured and have few metadata describing the content. Searching the relevant content would be a challenge. Because network cameras continuously produce data, processing must be able to handle the streaming data. This imposes stringent requirements of the performance. In this presentation, I will share the experience building a software system that aims to explore the opportunities using the data from global network cameras. CAM2 (Continuous Analysis of Many CAMeras, https://cam2.ecn.purdue.edu/) is cloud-based system for studying the worldwide phenomena using network cameras. CAM2 provides an event-based API (application programming interface) and is open to researchers to analyze the data for their studies. The web interface allows users to select the cameras for analysis. The cloud computing engine can scale in response to the needs of analysis programs.
Biography:
Yung-Hsiang Lu is an associate professor in the School of Electrical and Computer Engineering of Purdue University. He is an ACM distinguished scientist and ACM distinguished speaker. He is the lead investigator of a software system for analyzing thousands of network cameras worldwide. This cloud-based system can retrieve and analyze real-time visual data. More than 200 people have signed up as users. He is the lead organizer of the first Low-Power Image Recognition Challenge in 2015. He obtained the Ph.D. from Stanford University.
This Seminar is open to the public free of charge.
*For further information, please contact Dr. Honggang Wang at 508.999.8469, or via email at hwang1@umassd.edu.
Contact:
ECE: Electrical & Computer Engineering Department 508.999.9164 http://www.umassd.edu/engineering/ece/
Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering