Analyzing Big Visual Data in Global Network Cameras- Rethink Computer Vision
|Title:||Analyzing Big Visual Data in Global Network Cameras- Rethink Computer Vision|
|Date:||June 24, 2019 (Monday)|
|Time:||11:00 am - 12:00 pm|
|Venue:||Room 121, 1/F, Ho Sin-Hang Engineering Building, The Chinese University of Hong Kong, Shatin, N.T.|
|Speaker:|| Prof. Yung-Hsiang Lu
Computer vision relies vast amounts of data and labels for training and validation. Creating datasets and labels require significant efforts. A team at Purdue University creates datasets using network cameras that can provide real-time visual data. These cameras can continuously stream live views of national parks, zoos, city halls, streets, university campuses, highways, shopping malls. The stationary cameras (some of them have PTZ, pan-tilt-zoom) have contextual information (such as time and location) about the visual data. By cross-referencing with other sources of data (such as weather and event calendar), it is possible to label the data automatically. The run-time system allocates and adjusts computing resources as needed. This system is a foundation for many research topics related to analyzing visual data, such as (1) whether today's technologies are ready analyzing the versatile data, (2) what computing infrastructure is needed to handle the vast amount of real-time data, (3) where are the performance bottlenecks and how hardware accelerators (such as GPU) can improve performance, (4) how can this system automatically produce labels for machine learning.
Yung-Hsiang Lu is a professor in the School of Electrical and Computer Engineering and (by courtesy) the Department of Computer Science of Purdue University. He is an ACM distinguished scientist and ACM distinguished speaker. He is a member in the organizing committee of the IEEE Rebooting Computing Initiative. He is the lead organizer of Low-Power Image Recognition Challenge. Dr. Lu and three Purdue students founded a technology company using video analytics to improve shoppers' experience in physical stores. This company receives two Small Business Innovation Research (SBIR-1 and SBIR-2) grants from the National Science Foundation.
Enquiries: Ms. Shirley Lau at tel. 3943 8439
For more information, please refer to http://www.cse.cuhk.edu.hk/en/events