A Distributed Framework for Spatio-Temporal Analysis on Large-Scale Camera Networks

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 employ...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Proceedings - International Conference on Distributed Computing Systems Workshops s. 309 - 314
Hlavní autoři:	Kirak Hong, Voelz, Marco, Govindaraju, Venu, Jayaraman, Bharat, Ramachandran, Umakishore
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 01.07.2013
Témata:	Algorithm design and analysis camera networks Cameras distributed programming framework Face Programming resource management Runtime runtime system Smart cameras spatio-temporal analysis Streaming media
ISSN:	1545-0678
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Popis
Shrnutí:	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.
ISSN:	1545-0678
DOI:	10.1109/ICDCSW.2013.44