DocumentCode :
2186302
Title :
Teaching large-scale image processing over worldwide network cameras
Author :
Su, Wei-Tsung ; McNulty, Kyle ; Lu, Yung-Hsiang
Author_Institution :
Department of Computer Science and Information Engineering, Aletheia University, New Taipei City, Taiwan
fYear :
2015
fDate :
21-24 July 2015
Firstpage :
726
Lastpage :
729
Abstract :
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.
Keywords :
Cameras; Computer vision; Education; Image edge detection; Internet; Streaming media; DSP education; big data; image processing; real-time;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing (DSP), 2015 IEEE International Conference on
Conference_Location :
Singapore, Singapore
Type :
conf
DOI :
10.1109/ICDSP.2015.7251971
Filename :
7251971
Link To Document :
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