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Omron's HVC System to Offer Better Human Face Recognition
Omron launches a built-in human condition recognition unit Human Vision Components system for better human recognition

By
Apac CIOOutlook | Wednesday, August 31, 2016
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FREMONT, CA: Omron, an industrial automation company, launches a built-in human condition recognition unit “Human Vision Components” (HVC) system for better human recognition. The latest hardware, HVC-P2 B5T-007001 Series can clock a maximum speed of 10 times compared to its preceders.
The HVC inhibits “OKAO Vision” technology to identify human face expression, gender, age, gaze and blink into a camera module. The HVC-P2 has recognised a maximum speed of 10 times compared to its previous models. The new developments can identify a human body four times per second along with keeping a track of the person within a detection area.
The company offers HVC in two flavours, a long-distance detection type camerahead and a wide-angle detection type camera head. The long-distance type of the HVC-P2 can identify the presume attributes, including age and gender, along with the face expressions from a height of 3 meters. The wide angle detection machine can cover an area 100 cm by 75 cm from a distance of 50 cm. The stored data can later be used for optimum product refill, new product development and marketing activities.
The HVC-P2 is embedded with an equipment to identify the arrival of a user in its area. The user doesn’t know about the installation of camera in that area making it suitable for user’s attributes.
Features of HVC
The HVC-P2 comes up with a camera and a separate main board, connected via a flexible flat cable which can be installed on the edge of a flat unit display. The different image sensing functions available to identify human conditions includes face detection, human body detection, hand detection, face direction estimation, gaze estimation, blink estimation, age estimation, gender estimation, expression estimation, (five facial expressions: neutral, happiness, surprise, anger & sadness) and face recognition. The output image can be chosen from three types such as no image, 160*120 pixels and 320*240 pixels.