OpenCV Spatial AI Competition
Recently, the people at OpenCV launched the OpenCV Spatial AI competition sponsored by Intel as part of OpenCV’s 20th anniversary celebration. The main objective of the competition is to develop applications that benefit from the features of the new OpenCV AI Kit with Depth (OAK-D). The competition consists of two phases, the winners of the first phase were able to obtain an OAK-D for free to develop their application and the second phase winners will receive a cash prize of up to $3,000.
The OAK-D contains a 12 MP RGB camera for deep neural inference and a stereo camera for depth estimation in real time using Intel’s Myriad X Vision Processing Unit (VPU).
If you want to know more about the OAK-D, make sure to check theinterview by Ritesh Kanjee to Brandon Gilles**,**who is the Chief Architect of the OpenCV AI Kit.The kit has raised over $800,000 as part of their Kickstarter capaign with mote than 4,000 supporters. If you are interested, you can also find more about the kit in Luxoni’s community slack channel (https://luxonis-community.slack.com/)
Due to the interesting features that the OAK-D, I decided to apply for the OpenCV Spatial AI competition and was lucky enough to be selected as one of the winners of Phase 1. You can also check the projects for the rest of the Phase 1 winners here.
This publication is part of a series of post where I will be describing my journey developing with the new OAK-D as part of my competition project.
Proposed System
Illustration of how the output of the proposed system could detect people wearing a mask and their distance to the user.
The title of my proposal is “Social distancing feedback for visually impaired people using a wearable camera”. Due to the current worldwide outbreak of COVID-19, social distancing has become a new social norm as a measure to prevent the widespread of the pandemic.
However, visually impaired people are struggling to keep independence in the new socially distanced normal¹,². For blind people, it is not possible to easily confirm if they are keeping the social distance with the people around them. As an example, a** video in the Royal National Institute of Blind People (RNIB) Twitter account** showed the difficulties blind people are struggling with in their daily life due to social distancing.
Moreover, common solutions for the blind such as white cane or dog cannot assist the blind to keep the social distance. Even worse, blind people cannot know if the people close to them is wearing a mask or not, thus they suffer a higher risk of infection.
For those reasons, the objective of my project is to develop a feedback system for the blind that informs about the distance to other people around and whether someone is not wearing a mask.
#azure-kinect #deep-learning #opencv #covid19 #blind #deep learning