CHANCCTV expands ToF lens lineup for facial recognition and AI projects
Fuzhou ChuangAn Optics says its time-of-flight lens portfolio is built to support facial recognition, gesture control, depth sensing, and other AI vision projects. The company is emphasizing model-level specs, sample testing, and customization as engineering teams look to match optics with 940 nm ToF sensor systems.
Why it matters: - Facial recognition and AI vision systems depend on stable depth data at the optical level, not just software. - Matching a ToF lens to the sensor, wavelength, field of view, and operating conditions affects depth accuracy, spoof resistance, and recognition reliability. - For engineering teams, verifiable lens specs and sample testing can shorten the path from concept to prototype.
What happened: - Fuzhou ChuangAn Optics Co., Ltd. highlighted its CHANCCTV ToF lens portfolio for facial recognition and artificial intelligence projects. - The lineup covers 1/2-inch and 1/3-inch sensor formats, compact M12 mounts, multiple focal lengths, and 940 nm bandpass options. - The company says the lenses have been used in depth measurement, skeleton recognition, motion capture, and automotive sensing. - CHANCCTV said it supports buyers with model-level specifications, application guidance, and customization for sensor integration and calibration. - The company directed readers to the official website for product inquiries and custom optical consultations.
The details: - CHANCCTV said its ToF lens development focuses on sensor format compatibility, focal length, aperture, horizontal field of view, wavelength transmission, and thermal stability. - The current product lineup supports 1/2-inch and 1/3-inch sensors and sensing resolutions up to 5 MP. - Focal lengths range from 1.62 mm to 7.76 mm. - Horizontal field of view options range from about 48° to 109°. - The company said these M12 ToF lens configurations are aimed at different working distances and depth-camera designs. - CHANCCTV said final depth accuracy depends on the lens, sensor, illuminator, calibration, and processing algorithms working together. - For 940 nm systems, CHANCCTV pointed to the CH3731C as a model-level example. - The CH3731C is built for 1/3-inch sensors, has a 3.3 mm focal length, an F1.1 aperture, a 74.5° HFOV, a BP940 nm filter, and an M12 mount. - The CH3731C is rated for operating temperatures from -20°C to 85°C. - CHANCCTV said project teams still need module-level testing to confirm working range, depth accuracy, modulation frequency compatibility, and eye-safety standards. - The company said its application context includes iris recognition, smart homes, VR/AR, automotive ADAS, CCTV, and surveillance. - CHANCCTV said its product development and manufacturing focus dates to 2010. - The company said it offers selectable models, test samples, datasheets, and system test indicators for evaluation. - CHANCCTV said standard components can be ordered with one-piece samples and no minimum order quantity. - Stock samples are typically available in about 3 days, and the company said it responds to inquiries within 24 hours.
Between the lines: - The pitch is less about a single lens and more about reducing integration risk for depth-sensing systems. - CHANCCTV is positioning optical validation as the first hurdle before algorithm tuning and full module calibration. - The emphasis on samples, datasheets, and custom parameters suggests the company is targeting engineering teams rather than end users.
What's next: - Buyers are expected to submit sensor model details, active area dimensions, illumination wavelength, working range, target FOV, aperture, mount type, temperature range, depth accuracy goals, calibration method, and production volume. - CHANCCTV says engineering teams can use sample testing and physical depth validation before committing to larger builds. - The company is looking to convert specification screening into custom lens selection and prototype verification.
Disclaimer: This article was produced by AGP Wire with the assistance of artificial intelligence based on original source content and has been refined to improve clarity, structure, and readability. This content is provided on an “as is” basis. While care has been taken in its preparation, it may contain inaccuracies or omissions, and readers should consult the original source and independently verify key information where appropriate. This content is for informational purposes only and does not constitute legal, financial, investment, or other professional advice.
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