Using the "Eye Detection Technology" (RGB version), you can detect "blinking," "viewing distance," and "eye feature points" with a webcam.
The "joint patent technology" and "eye detection technology (RGB version)" utilizing "deep learning" developed in collaboration with Panasonic and our company is a highly versatile elemental technology that allows for easy measurement of "blinking," "eye feature points," and "viewing distance (the distance from the camera to the eye)" using web cameras and device cameras on PCs. The detection uses a learning model based on deep learning, and we have compressed the learning model to achieve a processing speed of 50 to 60 ms per frame even with CPU processing (on our company's Windows machine with an 8th generation Core i7 CPU). We offer an SDK and an application, and the application supports CSV output and recording functions, making it capable of handling not only real-time verification. The application is available in both "camera input version" and "file input version."
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Features of "Eye Detection/Blink Detection Technology" 1. Usable easily with WEB cameras/smartphone cameras Developed to be usable with familiar "visible light cameras (RGB)." (Glasses can be worn) 2. Capable of detecting "blinks," "viewing distance," and "presence of glasses" By detecting eye feature points and estimating viewing distance for each frame, it becomes possible to detect "blinks." Additionally, it can determine whether glasses are present and whether they are clear lens glasses or sunglasses. 3. Unique algorithm x deep learning (mask-friendly) By combining a unique "image processing method and detection algorithm" with deep learning, we have achieved high-precision detection of information related to human eyes. Detection is also possible while wearing a mask. 4. Optimized for edge AI, a deep learning model that can process quickly using only CPU By compressing the deep learning training model as much as possible, it can process quickly without a GPU. With recent Core i5/i7 processors, processing can be achieved at 50-60ms per frame.
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Applications/Examples of results
◆Uses - Various applications for detecting blinks - Various applications for measuring the distance between the eyes and smartphones or PCs
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We are researching and developing element technologies related to human sensing using image processing techniques based on deep learning, and providing them. ◆ Impersonation Detection Technology This technology combines fake detection, which determines whether a face in a photo or smartphone is fake or real, and action detection, which assesses whether a user is performing the instructed action or impersonating someone. https://bio-check.pas-ta.io/ ◆ Eye Detection/Blink Detection Technology This highly versatile element technology allows for easy measurement of "blinks," "eye feature points," and "viewing distance (the distance from the camera to the eye)" using a webcam or PC device camera. https://pupil.pas-ta.io/ ◆ Gaze Detection Technology This technology analyzes camera input or video files to detect a person's "gaze direction" and "face orientation." https://eyetrack.pas-ta.io/ ◆ Iris Authentication Technology This authentication technology uses the unique pattern of the "iris" in a person's eye, which does not overlap with others. Currently, it is only provided to partners involved in the joint development of iris capture cameras. https://iris.pas-ta.io/