17060

Large-scale image analysis using docker sandboxing

B. Sengupta, E. Vazquez, M. Sasdelli, Y. Qian, M. Peniak, L. Netherton, G. Delfino
Cortexica Vision Systems Limited, London SE1 8RT, UK
arXiv:1703.02898 [cs.CV], (7 Mar 2017)

@article{sengupta2017largescale,

   title={Large-scale image analysis using docker sandboxing},

   author={Sengupta, B and Vazquez, E and Sasdelli, M and Qian, Y and Peniak, M and Netherton, L and Delfino, G},

   year={2017},

   month={mar},

   archivePrefix={"arXiv"},

   primaryClass={cs.CV}

}

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With the advent of specialized hardware such as Graphics Processing Units (GPUs), large scale image localization, classification and retrieval have seen increased prevalence. Designing scalable software architecture that co-evolves with such specialized hardware is a challenge in the commercial setting. In this paper, we describe one such architecture (Cortexica) that leverages scalability of GPUs and sandboxing offered by docker containers. This allows for the flexibility of mixing different computer architectures as well as computational algorithms with the security of a trusted environment. We illustrate the utility of this framework in a commercial setting i.e., searching for multiple products in an image by combining image localisation and retrieval.
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