Eyes on Edge: tinyML Vision Challenge!

We are giving away $6,000 in prizes to the top three submissions. Judges will score your projects based on the judging criteria outlined in the rules tab. An additional $1,000 in honorable mention prizes have been added by the judges.

Kwabena Agyeman

Co-founder of OpenMV, a company dedicated to making machine vision on microcontrollers easy. The OpenMV Cam makes it possible for students and hobbyists to build simple robots that can track colored objects or faces. For example, with the OpenMV Cam and a Nerf Gun engineering, major college students can build a color tracking turret for a mechatronics capstone project.

Jay Burris

Academic Program Manager at Intel who has been working in the embedded, automotive, and Internet of Things industry for 20+ years. He is passionate about advocating for AI developers, students and faculty to help them advance their knowledge using Intel Technologies such as the AI toolkit called Intel®️ Distribution of OpenVINO™️ toolkit, learning through Intel’s new Edge AI Certification program, and prototyping ideas inside the cloud developer environment Intel® DevCloud for the Edge.

Evgeni Gousev

Senior Director, at Qualcomm responsible for leading HW/SYS research and development, ultra-low power edge computing platform and machine vision, tinyML foundation member and advocate

Samuel Kuo

Senior Director, R&D for ASIC development at Himax Technologies Inc., with responsibility for ultra-low power Endpoint AI processor and ecosystem development.

Zach Shelby

An entrepreneur, angel investor and technologist in the embedded space with a passion for TinyML, embedded and Internet engineering. Zach is a former Arm VP, founder and CEO of the Micro:bit Foundation and Sensinode, active in several of his portfolio companies, and is working to bring ML to any embedded device as co-founder and CEO of Edge Impulse.

Complimentary & Discounted Hardware

In order to accelerate your development, tinyML Vision Challenge sponsors have made complimentary and discounted hardware available. Here is what is currently available:

Intel and Luxonis are pleased to offer a 50% discount on a DepthAI LUX-ESP32 to the first 50 project idea submissions. We want to hear your ideas! $100 discount to LUX-ESP32 DepthAI Embedded SOM with WiFi, BT, IMU, and On-Board Cameras ($99 after 50% discount). Provide a description of a real-world spatial AI computer vision problem and proposed solution. Use of AI with the OpenVINO™ toolkit and spatial depth sensing are encouraged. Please submit your project idea proposal, detailing how your solution idea will use the Luxonis LUX-ESP32 DepthAI Embedded Camera using OpenCV and AI acceleration with the Intel® Distribution of OpenVINO™ toolkit. Submissions are due by July 8th, 2021 at noon PDT. Must be registered for the tinyML Vision Challenge to qualify for discount, and be one of the first 50 to submit a project idea. Submit your request for a discount while supplies last!

Pixart Imaging has a limited supply of complimentary PAJ6100U6 OpenMV Shields for use on the Open H7 platform. To request a shield please send email to sales@pixart.com with the subject "PAJ6100U6 OpenMV Shield".

Videos

• Autonomous Driving with OpenMV and Edge Impulse
• Arm Innovation Coffee: tinyML on OpenMV with Edge Impulse
• Arm Innovation Coffee: Embedded Machine Vision with Arduino Portenta
• Supporting Tensorflow Lite MCU in tiny low power FPGAs
• Intel & Luxonis AI-Powered Backpack Helps Visually Impaired Navigate World (also article)
• Luxonis YouTube channel
• OpenVINO™ toolkit video series and YouTube channel

Tutorials & Guides

• Connecting the OpenMV Cam H7 to Edge Impulse
• Connecting the Himax WE-I Plus to Edge Impulse
• Getting Started with the Himax WE-I Plus
• Connecting the Portenta and Vision Shield to Edge Impulse
• Connecting the Eta Compute ECM3532 AI Vision Board to Edge Impulse
• Getting Started with Lattice sensAI
• Object detection on Lattice FPGA
• Predictive maintenance on Lattice FPGA
• Learning more about DepthAI
• Getting Started with DepthAI
• Luxonis Open Source Hardware Designs on Github
• Learn and Develop AI with the OpenVINO™ toolkit using the Intel® DevCloud for the Edge… free registration and access
• Download the OpenVINO™ toolkit

Webinars

• AI Vision and Sensor Fusion with Himax WE-I Plus
• Ultra-Low-Power Computer Vision Applications on the Portenta
• Ultra-Low-Power Computer Vision Applications with Edge Impulse and the Eta Compute AI Vision Board

tinyML Talks

• Yung-Hsiang Lu: Low-Power Computer Vision
• Aravind Natarajan: Pushing the Limits of Ultra-Low-Power Computer Vision for tinyML Applications
• Hans Reyserhove: Embedded Computer Vision Hardware Through the Eyes of AR/VR

The inaugural tinyML Summit in March 2019 showed very strong interest from the community with active participation of senior experts from 90 companies. It revealed that: (i) tiny machine learning capable hardware is becoming “good enough” for many commercial applications and new architectures (e.g. in-memory compute) are on the horizon; (ii) significant progress on algorithms, networks and models down to 100kB and below; and (iii) initial low power applications in the vision and audio space. There is growing momentum demonstrated by technical progress and ecosystem development.