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ViCoS Eye - a webservice for visual object categorization
In our paper we present an architecture for a system capable of providing back-end support for webservice by running a variety of computer vision algorithms distributed across a cluster of machines. We divide the architecture into learning, real-time processing and a request handling for web-service. We implement learning in MapReduce domain with Hadoop jobs, while we implement real-time processing as a Storm application. An additional website and Android application front-end are implemented as part of web-service to provide user interface. We evaluate the system on our own cluster and show that the system running on a cluster of our size can learn Caltech-101 dataset in 40 minutes while real-time processing can achieve response time of 2 seconds, which is adequate for multitude of online applications.