Name
Title | ||
|---|---|---|
An Empirical Study on Big Video Data Processing: Architectural Styles, Issues, and Challenges |
Abstract | ||
|---|---|---|
Video data contributes to the majority of big data, henceforth, how to efficiently and effectively discovering knowledge from large-scale video data becomes a crucial challenge. In this paper, we propose multiple architectural styles for the domain of large-scale video data analytics services. These styles include online combined with offline processing style, distributed shared repositories, image mining and prediction services with deep learning techniques. These architectural styles are successfully implemented and examined in a number of domains including smart traffic and smart drones, as demonstrated in a middleware developed specifically for large-scale continuous video data processing. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IIKI.2016.7 | 2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI) |
Keywords | Field | DocType |
Cloud Computing,big video data processing,architecture styles,Smart City | Middleware,Data processing,Data analysis,Computer security,Computer science,Smart city,Artificial intelligence,Deep learning,Multimedia,Big data,Empirical research,Cloud computing | Conference |
ISBN | Citations | PageRank |
978-1-5090-5953-9 | 0 | 0.34 |
References | Authors | |
7 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weishan Zhang | 1 | 396 | 52.57 |
| Zhichao Wang | 2 | 6 | 5.56 |
| Liang Xu | 3 | 57 | 14.47 |
| Dehai Zhao | 4 | 27 | 3.72 |
| Faming Gong | 5 | 22 | 5.90 |
| Qinghua Lu | 6 | 145 | 18.63 |