Name
Abstract | ||
|---|---|---|
Cameras are becoming ubiquitous. Applications including video-based surveillance and emergency response exploit camera networks to detect anomalies in real time and reduce collateral damage. A well-known technique for detecting anomalies is spatio-temporal analysis -- an inferencing technique employed by domain experts (e.g., vision researchers) to answer spatio-temporal queries. In this paper, we propose a distributed framework that facilitates the development and deployment of spatio-temporal analysis applications on large-scale camera networks and backend computing resources. We make the following contributions: (a) an investigation of the computation/communication costs associated with spatio-temporal analysis, (b) a programming framework designed for large-scale spatio-temporal analysis, and (c) performance evaluations for each step of the spatio-temporal analysis with realistic algorithms. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICDCSW.2013.44 | ICDCS Workshops |
Keywords | Field | DocType |
distributed programming framework,spatio-temporal analysis,programming framework,large-scale spatio-temporal analysis,spatio-temporal query,camera network,backend computing resource,well-known technique,anomaly detection,video-based surveillance,camera networks,resource management,ubiquitous computing,emergency response,distributed framework,large-scale camera networks,spatio-temporal analysis application,runtime system,inferencing technique,distributed processing,large-scale camera network,video surveillance,algorithm design and analysis,programming,face,smart cameras | Software deployment,Algorithm design,Computer science,Spatio-Temporal Analysis,Smart camera,Real-time computing,Exploit,Ubiquitous computing,Software framework,Runtime system,Distributed computing | Conference |
ISSN | ISBN | Citations |
1545-0678 | 978-1-4799-3247-4 | 1 |
PageRank | References | Authors |
0.43 | 10 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kirak Hong | 1 | 218 | 13.15 |
| Marco Voelz | 2 | 1 | 0.43 |
| Venu Govindaraju | 3 | 3521 | 422.00 |
| Bharat Jayaraman | 4 | 509 | 50.19 |
| Umakishore Ramachandran | 5 | 1071 | 103.27 |