{"id":24520,"date":"2024-05-27T16:21:33","date_gmt":"2024-05-27T14:21:33","guid":{"rendered":"https:\/\/ggba.swiss\/?p=24520"},"modified":"2024-05-27T16:21:34","modified_gmt":"2024-05-27T14:21:34","slug":"csem-unveils-energy-efficient-emotion-recognition-system-moody","status":"publish","type":"post","link":"https:\/\/ggba.swiss\/en\/csem-unveils-energy-efficient-emotion-recognition-system-moody\/","title":{"rendered":"CSEM unveils energy-efficient emotion recognition system MOODY"},"content":{"rendered":"\n

CSEM<\/a> has announced the launch of MOODY, a groundbreaking vision system that can detect human emotions with minimal power consumption. This innovative system operates on a sub-milliwatt (sub-mW) power level, enabled by a single coin cell battery, making it a game-changer for human-machine interaction (HMI), access control, and driver safety applications.<\/p>\n\n\n\n

Envision a world where devices can understand and react to human emotions, all while consuming negligible amounts of energy. CSEM is making this a reality with MOODY, a sensor that challenges the traditional energy demands of machine learning (ML) applications.<\/p>\n\n\n\n

\u201cCentral to MOODY is CSEM\u2019s ERGO640 high dynamic range (HDR) image sensor<\/a> and Visage ML accelerator<\/a>\u2014technological marvels that empower MOODY to process data directly at the source with unparalleled energy efficiency,\u201d explained Dr. Petar Jokic, Senior R&D Engineer at CSEM. \u201cThese components, in harmony with advanced embedded learning algorithms and resource-efficient software, render MOODY an ideal candidate for spearheading the future of next-generation ULP ML and HMI applications.\u201d<\/p>\n\n\n\n

The three pillars of MOODY<\/h4>\n\n\n\n

The ERGO640 high dynamic range (HDR) imager is a key component of MOODY. It uses a patented time-domain pixel-level analog-to-digital (A\/D) conversion architecture, which captures a wide range of light intensities to ensure accurate imaging even in challenging lighting conditions. Consuming less than 1 milliwatt (mW) for VGA resolution at 10 frames per second (FPS), the ERGO640 is crucial for battery-operated devices. With a pixel pitch of 6.3 micrometers (\u00b5m) and a fill factor of 83%, the ERGO640\u2019s on-chip frame memory and adaptable interfaces ensure compatibility with resource-limited microcontrollers (\u00b5C), making it ideal for energy-efficient applications.<\/p>\n\n\n\n

The Visage ML system-on-chip is another cornerstone of MOODY. This intelligent processor operates at sub-mW power levels, combining a binary decision tree (BDT) engine for object detection with a multi-precision convolutional neural network (CNN) engine for complex classification tasks. This versatility allows the chip to efficiently handle various ML workloads. Supporting comprehensive end-to-end edge processing, this chip enables always-on image analysis within a sub-mW power budget, which is perfect for continuous operation in wearables and access control devices.<\/p>\n\n\n\n

MOODY\u2019s success is not just hardware-based as it also relies on meticulously optimized software algorithms. CSEM has refined two neural network (NN) algorithmic blocks: one for efficient face detection and another for emotion recognition, requiring less than 300 kilobytes (KB) and 200 KB of memory, respectively.<\/p>\n\n\n\n

Innovations beyond MOODY<\/h4>\n\n\n\n

CSEM’s expertise in ultra-low-power vision systems and edge artificial intelligence goes well beyond the MOODY project. The company also offers eye-gaze and gesture tracking technologies<\/a> to enhance safety in autonomous aviation and vehicles. Their facial recognition technology<\/a> provides secure identification for access control and efficient human-machine interactions. Additionally, CSEM’s advanced vision technology<\/a> with edge processing<\/a> has the potential to significantly improve areas such as patient care, driver safety, and building management.<\/p>\n\n\n\n

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