NXP Semiconductors has released its offline vision solution, SLN-VIZN-IOT, a comprehensive, integrated development platform that includes a hardware module and the associated software required to implement offline face and expression recognition. Based on NXP’s i.MX RT106F crossover microcontroller, the company’s turnkey face and expression recognition solution enables original equipment manufacturers (OEMs) to quickly, easily and inexpensively incorporate face and expression recognition into a diverse range of Internet-of-Things (IoT) products.
The solution provides low latency and eliminates the need
for cloud connectivity, says NXP. In addition, it is designed to remove the
cost and overhead associated with an MPU-based system. The i.MX RT106F
leverages NXP’s vision processing engine to provide a breakthrough in price and
performance, using a neural network to perform face detection, recognition and
anti-spoofing. Developers can now take advantage of NXP’s MCU-based solution to
offer advanced human machine interface (HMI) capabilities that can anticipate
and personalize the end user’s experience with smart edge devices such as smart
appliances, thermostats, lighting, alarms and power tools.
The i.MX RT106F is an EdgeReady solution-specific member of the i.MX RT106F family of crossover MCUs, targeting low cost embedded face recognition applications. It features NXP’s advanced implementation of the Arm Cortex-M7 core, which operates at speeds up to 600MHz. The i.MX RT106F processor is licensed to run NXP’s turnkey face and emotion recognition software solution, which includes image capture and pre-processing, face detection, alignment and recognition, with anti-spoofing and many additional features. In addition to delivering the face recognition capability, the i.MX RT106F MCU can also be used as the main microcontroller in most IoT product implementations.
The SLN-VIZN-IOT development kit is available now, priced
at an MSRP of $199 USD.
NXP Semiconductors | www.nxp.com
![Figure 1 Blockchain network and programming concept [2]](https://i0.wp.com/circuitcellar.com/wp-content/uploads/2021/10/374_TTF_Golata_Figure_1.jpg?resize=145%2C100&ssl=1)
