The face recognition demo shows person facial feature training via a single photo and subsequent face matching on the live video stream, using VisionLabs’ library integrated onto the H22 System on a Module (SoM).

The H22 SoM, designed in-house, is a power-efficient camera platform for high-resolution video encoding and live video streaming. The core of the SoM platform is an Ambarella H22S85N™ System on a Chip that integrates an advanced image processing pipeline, H.265 (HEVC) and H.264 (AVC) encoders , and a powerful Quad core ARM® Cortex™-A53 CPU for advanced business logic like computer vision, flight control, WiFi streaming, and other user applications. The H22 SoM is supplied with the SoM SDK – a Linux-based toolchain that allows executing user-level applications on the ARM core. To speed up the development process, there are a series of reference code samples for the SoM SDK.

The demo system implements a face training scenario using a simple mobile app. A single photo, captured through a mobile phone and added to the database, is quite enough for the NN to learn. Photos with name tags stored in the mobile app are transferred via WiFi onto the SoM to extract face descriptors and carry on with the recognition scenario. Recognition occurs in real-time on faces detected in the camera’s field of view. The markup is straightforward: red frames and “Unknown” tags for the people that are not found in the database, green frames and a nametag for the people from the database, and grey frames without a tag for the stage when the person’s face is found but is still being processed by the recognition algorithm.

This basic face detection and tracking algorithm was put together for demo purposes. More robust solutions are to be selected for more practical usage scenarios. One such solution will be in an upcoming post.

Despite being only a demo implementation, the high resolution and decent image quality enables precise face detection and recognition with indoor lighting in overcrowded conditions. Face recognition capabilities could be a value-added feature for security applications such as seamless entry control.