Improved facial classification accuracy

To date, BrainChip Studio utilised spiking neural networks to enable facial classification on partial faces. This partial-face mode is useful in situations where the probe image or the extracted faces may be obscured due to hats, masks, scarves or camera angle.

BrainChip Studio 2018.3 uses a full-face mode to perform facial classifications. In situations where the entire face is visible in the probe image or in the extracted faces, this new mode provides a significant increase in facial classification accuracy. Depending on the dataset used, testing indicates this mode provides a ten to thirty percent improvement in accuracy, without impacting throughput.

According to MarketsandMarkets, the facial recognition market is expected to be over $7bn by 2022. BrainChip Studio’s unique facial classification technology works in environments where traditional biometric-based face recognition systems fail, including low-light, low-resolution, and visually-noisy environments. BrainChip Studio is primarily used by law enforcement, intelligence, and counter-terrorism agencies that use existing CCTV infrastructure.

“We are always looking for ways to continually improve our products by listening to our customer requests,” said Bob Beachler, BrainChip’s Senior Vice President of Marketing and Business Development. “Not surprisingly, improving accuracy is typically at the top of list for video analytic software. With BrainChip Studio 2018.3 we were able to provide a dramatic increase in accuracy.”

BrainChip Studio 2018.3 is currently available.