Team VIThinkers - Oculus

dwij2812 commented 5 years ago

ℹ️ Project information

Project Name: Oculus
Short Project Description: Virtual eye for the Blind
Team Members: Dwij Sukeshkumar Sheth (@dwij2812), Shantanu Singh (@shan1322), Siddharth Jain (@sid25298)
Demo Link: https://dwij2812.github.io/Oculus/
Repository Link: https://github.com/dwij2812/Oculus
Labels: Open Innovation, Open Innovation - No Track Followed

🔥 Your Pitch

In order to complete day-to-day activities effectively and efficiently, Technology plays vital role in human life. Especially, Assistive Technology devices support to differently abled people, in order to live their life very comfortably. Realizing the importance of Assistive Technology, this product idea gives comprehensive solution for the blind people and provide them an end to end solution. With the power of embedded systems and advanced Artificial Intelligence techniques applied to the field of computer vision we aim to make a Hat/cap that can help the blind perceive the world around them. Oculus harnesses the power of AI to describe people, text and objects. It can tell visually-impaired persons, what is around them. If the camera on the hat is pointed at a park, the device can describe how the scene looks like. Oculus is made using a camera module which will be mounted on the cap in order to capture images of the world around the person which will be interfaced with an SBC (Raspberry Pi). Using advanced analytics and several machine learning algorithms for image segmentation like YOLO, CNNs (Convolutional Neural Networks) we have process the image using a trained model and narrate the scene in the picture to the user in real-time. Once the analytics part is done the image description so created is converted into speech format and sent to the audio device like a speaker, earphone so that the user can hear the description about it. This process is carried out repeatedly again and again at fixed intervals and sent to the user. The device is planned to be built on a cap to make it easy to use and trendy. The system will be powered by a rechargeable LiPo battery that is light weight and easy to mount on the cap. Further features like smartphone connectivity, safety features and ambience monitoring can be added to the cap and connect it with the cloud services so that the known contacts of the person can get to know any emergency situations or alerts immediately. Oculus uses frameworks like TensorFlow and Keras along with OpenCV in order to train and run the machine learning models that are used for the image captioning. Apart from that the Gtts (Google text to speech) library is used to convert the captions so generated into audio files which can be presented to the user for a hassle-free UX.

🔦 Any other specific thing you want to highlight?

Easy to use
Minimal hardware setup required
Cost effective solution (Prototype cost: INR 4000, Expected production cost: INR 2500)
Accurate and Reliable
Hassle free UX

✅ Checklist

Before you post the issue:

[x] You have followed the issue title format.
[x] You have mentioned the correct labels.
[x] You have provided all the information correctly.

yashovardhan commented 5 years ago

@dwij2812 please mention the correct labels.

Please go through the README.md file for more information about the labels.

dwij2812 commented 5 years ago

@dwij2812 please mention the correct labels.

Please go through the README.md file for more information about the labels.

Done

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