ELECTRONIC MATERIAL
FP-AI-FACEREC1: Lowering
the Barrier to Machine Learning Reveals New Applications The FP-AI-FACEREC1 Function Pack is now available ondemand, thus enabling ST’s community to run new applications leveraging facial recognition on an STM32H7, thanks to its use of STM32Cube.AI. The package offers a binary for the STM32H747I-DISCO board and ST’s B-CAMS-OMV camera adapter board. The latter provides an extension connector for OpenMV and Waveshare camera modules. The software handles on-device enrollment, camera control, interfaces, joysticks on the board, image capture, pre-processing, and the machine learning library. Its database can store up to 100 users, and the process runs at 3.6 frames per second on the embedded RAM and flash. As a result, it’s possible to conceive an application that would not require external memory. Moreover, the solution only needs a low-resolution RGB camera, regular ambient lighting, and subjects at up to 1.5 meters (5 feet).
The New Price of Admission
During a roundtable with The ST Blog, a design house shared how customers increasingly want to benefit from AI. However, the barrier to entry is still high. Developing AI models for resource-constrained microprocessors may increase overall costs, and the necessary reliance on data scientists means smaller teams are at a disadvantage. FP-AI-FACEREC1 is,
therefore, critical because it shows that it is possible to run a complex neural network algorithm on a microcontroller. Additionally, ST software tools help alleviate some of the inherent complexities to lower the barrier to entry. Put simply, the price of admission to AI just became an STM32 Discovery Kit since all development software works with free ST tools such as STM32CubeIDE and STM32CubeMonitor.
FP-AI-FACEREC1, a New Chapter in the Market Penetration of Machine Learning Machine Learning Is Becoming a Necessity The new ST Software package opened the door to applications that can benefit from artificial intelligence but can’t justify massive investments. When smartphones started authenticating users by scanning faces, manufacturers had to inject a lot of cash and manpower. The need for extreme accuracy and the stringent security certifications that govern such use cases demand
42 09 | 2021 BISinfotech
