Presented by:

D964b48ba3c3366cc967250087401257

Jorge Hidalgo

from Accenture

Jorge Hidalgo is the Global Java Professional Community Co-Lead in Accenture, and the Custom Distributed, Java, Architecture and DevOps Capability Lead in the Accenture Delivery Center in Spain (SDC). Besides Professional Community and Capability work, Jorge dedicates a portion of his time in various architectural and management roles, helps projects through services as the Accenture Discovery and Diagnostic Service and Accenture Architecture Excellence, participates in proposals/orals and supports projects in their adoption of cutting edge technologies and architectures. He is a global Architecture, Cloud, Java and DevOps SME that frequently writes and speaks about software development, quality and testing topics, internally in Accenture through blogs and webinars, publicly through his blog at http://deors.wordpress.com and in conferences like JavaOne, OpenSlava and Red Hat Developer Day. Follow him on Twitter: @_deors

No video of the event yet, sorry!

Face recognition has countless applications in a lot of different fields, from security to marketing. But it usually requires expensive hardware or proprietary software solutions. During this session we are going to describe the architecture and implementation of an face recognition platform based on low-cost board like Raspberry Pi and open source software like Java and OpenCV, and an example implementation on that platform providing functionality to count faces. This solution could be useful to control the access to enclosed spaces such as rooms with limited capacity. The solution combines cameras, Raspberry Pi, OpenCV, MQTT, embedded Java and Java SE to fulfill the requirements, including privacy concerns, scalability… and much more. This talk is an evolution of the talk with same title done in JavaOne San Francisco 2016.

Entrevista a Jorge Hidalgo en nuestro blog.

Date:
2017 May 6 - 19:00
Duration:
45 min
Room:
Sala Fuengirola
Conference:
Opensouthcode 2017
Language:
Track:
Difficulty:
Easy

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