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Hello @katource1 thank you for your comment. This video is about the new launch of FRAMOS Optical sensor modules FSM:GO with IMX687 sensor: www.framos.com/en/fsmgo If you have any questions feel free to reach out to our experts. :) Best regards, FRAMOS

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Hello @hossenwakhungu3366, thank you for your comment. We are glad you find them amazing. If you have any questions feel free to reach out to our experts at info@framos.com or via the contact form at www.framos.com

Hi Justin, we invite you to reach out to our experts at info@framos.com. They will be happy to assist you with the answer. 🙂

Hi @hossamalzomor3311, A good parallel to draw is between “lens's internal multipath” (LIM) and lens flare or glare. Lens flare is a superposition of the intensity of the target and the internal reflections of the lens system. LIM has the same structure but instead of a just a superposition of intensity we have a superposition of the phase of the LIM and the target. This superposition affects the measured phase angle based on angular and intensity difference between the LIM and target. Here’s how you can minimize the effects of LIM: 1 - The first step is to reduce as much as possible the presence of LIM by using good lenses and filters, where the dynamic range of the lens is optimized for the iToF laser wavelength. These HDR lenses have reduced glare/ 2 - Controlling the dynamic range of the scene. Eliminating retro-reflective materials where possible reduces the intensity of LIM artifacts. 3 - Advanced acquisition and processing to detect glare in the image and compensating for it in the image processing pipeline. This is deliberately vague as there are many techniques that can be applied in this realm... As an example: The use of sensor and laser combined HDR imaging; This can detect and quantify the source of glare in an image (assuming it is within the sensor FoV) and measure its phase angle and power. This together with an approximation of the lens's “flare susceptibility” can highlight the pixels that are directly affected as well as approximate the LIM phase offset for the entire array - for the “darker” objects within the scene. The FRAMOS iToF devkit does not include such a complex pipeline. It does, however, include a mode setting and raw data throughput to allow customers to build a processing pipeline as described.

Hello @alicezou8037, Thank you for your comment. :) Contact us at info@framos.com or via the contact form at www.framos.com to talk to our experts.

@@FRAMOS Thanks for your reply,please contact me if you need the components:) sales011@barumelectronics.com

“Thank you for your question. The video references an older version of the software and underlying API’s. We recommend you look at the dev.intelrealsense.com/docs/intel-realsensetm-d400-series-calibration-tools-user-guide the linked pdf available after this link was updated as recently as April 2021.”

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Yes, you can get camera parameters using intrisnsics functions like below // select the stream you want to know auto depthStreamProfile = profile.get_stream(RS2_STREAM_DEPTH).as<rs2::video_stream_profile>(); depthStreamProfile.get_intrinsics(); rs2_intrinsics calibration = depthStreamProfile.get_intrinsics() Where rs2_intrinsics is like below /** \brief Video stream intrinsics */ typedef struct rs2_intrinsics { int width; /**< Width of the image in pixels */ int height; /**< Height of the image in pixels */ float ppx; /**< Horizontal coordinate of the principal point of the image, as a pixel offset from the left edge */ float ppy; /**< Vertical coordinate of the principal point of the image, as a pixel offset from the top edge */ float fx; /**< Focal length of the image plane, as a multiple of pixel width */ float fy; /**< Focal length of the image plane, as a multiple of pixel height */ rs2_distortion model; /**< Distortion model of the image */ float coeffs[5]; /**< Distortion coefficients, order: k1, k2, p1, p2, k3 */ } rs2_intrinsics; Please see this reference link for a simple application that uses intrisnsics functions on the RealSense github : github.com/IntelRealSense/librealsense/blob/c3c758d18c585a237bb5b635927797aa69996391/examples/measure/readme.md

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