DocumentCode :
2092951
Title :
Running Interactive Perception Applications on Open Cirrus
Author :
Zhu, Qian ; Yigitbasi, Nezih ; Pillai, Padmanabhan
fYear :
2011
fDate :
12-13 Oct. 2011
Firstpage :
17
Lastpage :
21
Abstract :
Interactive perception applications, such as gesture recognition and vision-based user interfaces, process high-data rate streams with compute intensive computer vision and machine learning algorithms. Yet, they require extremely low latencies to remain interactive and ensure timely results to users. Cluster computing resources, such as those provided by Open Cirrus deployments, can help address the computation requirements, but significant challenges exist in practice. This paper highlights our efforts to parallelize interactive perception applications, tune them for best fidelity and latency, and place, schedule, and execute them on a cluster platform. We also look at remaining open problems and potential solutions.
Keywords :
cloud computing; computer vision; gesture recognition; interactive systems; learning (artificial intelligence); user interfaces; Open Cirrus; cluster computing resources; computer vision; gesture recognition; interactive perception applications; machine learning algorithm; vision-based user interfaces; Feature extraction; Programming; Servers; Streaming media; Throughput; Tiles; Tuning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Open Cirrus Summit (OCS), 2011 Sixth
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4673-0727-7
Type :
conf
DOI :
10.1109/OCS.2011.9
Filename :
6200549
Link To Document :
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