Building camera based intelligent applications
Submitted by Nabarun Pal (@palnabarun) on Saturday, 10 June 2017
Section: Crisp talk for data engineering track Technical level: Intermediate
Camera based intelligent applications are lot of fun! There are many practical applications of it like Industrial Counters, Real Time Object Tracking, Object Classification, Road Traffic Estimation etc. While they are fun and interesting, building them is not that trivial. Generally, building camera based intelligent applications require many modules in the pipelines and a data scientist may not be aware of those. It involves managing hardware, machine learning, a dashboard for user interaction and data visualization and most importantly a way to glue them all together. Taking care of all these requires a considerable amount of time to deploy an application.
I have been working on trying to build tools to simplify and streamline this process and allow data scientists to build such an application in days instead of weeks. In this talk, I will discuss about the approach we have taken, the tools that we have built, of which some are open source, and explain how these tools improved the overall time needed to build camera based intelligent applications.
The talk will be structured into 3 parts - 8-10mins for the presentation, 3-5mins for the hands-on demo to building an application from scratch and the rest for questions.
The presentation is structured as follows with details in slide link provided:
- About me
- Modules in a camera based application
a. Data Ingestion b. Pre-processing c. Machine Learning d. Dashboard
- Our approach
a. User agent on data capture device b. A tool to deploy ML functions - Firefly c. Modular dashboard components
In the hands on demo part, I will go through building one image/video based machine learning problem that a data scientist may want to make using our open source modules. I will show how to deploy the application on the rorocloud platform or on your own servers or local machine.
Basic knowledge of building blocks of a machine learning application. None in terms of hardware.
The speaker is Nabarun Pal, an undergraduate student at Indian Institute of Technology Roorkee who just finished his pre-final year. Currently, he is working for rorodata which aims at providing data scientists a platform to build and deploy their models without the need of worrying about infrastructure, scalability and performance.
He is passionate about software development. He can also talk about Internet of Things, Electronics, Robotics with equal spirit. His journey with the field of software and robotics started in his schooling days. He represents the college in various Robotics competitions and was involved in projects related to the above domains, brief of which can be found here