Custom Object Tracking With Windows 10 IOT core

Hardware components:
NVIDIA Jetson NVIDIA gpu gtx 750ti
× 1
logitech webcam c210
× 1
R8326274 01
Raspberry Pi 2 Model B
× 1
Software apps and online services:
Vs2015logo
Microsoft Visual Studio 2015
10
Microsoft Windows 10 IoT Core
Microsoft CNTK
Virtual DUB

Custom Object Tracking With Windows 10 IOT core

STORY

Hello

After a long time i decided to post another project as i was really bit by my success in my first project

I wanted to take things further and explore new Human to machine interaction models in IOT space

Hence i came up with this project

Problem that the POC aims to solve:-

Switches are sometimes hard to reach and many a times one is left with the longing for a switch to be much closer to reach .

Voice recognition to switch on/off an appliance is good but not really ok as you are required to continuously address the system in your voice.

Sometimes a person just wishes for a tactical feedback!.

Solution:-

  • Have 2 or more webcams around the room which keep monitoring the room.
  • Create a custom object .(This can be anything custom designed to even one which is designed specifically for room aesthetics )
  • Have the system machine learn what a custom switch looks like and let the location of the switch be decided by the user .
  • Have GPIO pins control relays which switch appliances on /off or interact with services

Due to above solution user is able to dynamically reconfigure physical location and services that the custom switches offer at will at the drop of a hat!

Training method:-

The system borrows from my old project accessible here

and hence forth i have created custom programs and utils for

  • Training with reference to only the object and not the scene
  • Retraining
  • Partial viewing of an object
  • Labeling Utility

Read More: Custom Object Tracking With Windows 10 IOT core

About The Author

Scroll to Top
Read previous post:
Embedded Systems Online Training Resources
Embedded Systems Online Training Resources

Online learning of embedded system and electronics in general still bounded, and this is mainly related to the nature of...

Close