Teaching Large-Scale Image Processing over Worldwide Network Cameras

被引：0

作者：

Su, Wei-Tsung ^{[1
]}

McNulty, Kyle ^{[2
]}

Lu, Yung-Hsiang ^{[2
]}

机构：

[1] Aletheia Univ, Dept Comp Sci & Informat Engn, New Taipei, Taiwan

[2] Purdue Univ, Sch Elect & Comp Engn, W Lafayette, IN 47907 USA

来源：

2015 IEEE INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP) | 2015年

基金：

美国国家科学基金会;

关键词：

image processing; big data; DSP education; real-time;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a software system for large-scale image processing. Through this system, students may choose to analyze the images from several thousand network cameras deployed worldwide. This system allows both real-time analysis of live data or storing the data for off-line analysis. This system currently supports image processing using OpenCV-Python. The system allocates cloud instances as the computational engine and, as a result, allows users to analyze the images from many cameras simultaneously. The system demonstrates the ability to process 5,000 images from 500 cameras for lane detection in less than 2 minutes.

引用

页码：726 / 729

页数：4