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In 2018, I was responsible for the production line camera setup of stereo camera calibration, and to ensure the performance of stereo camera calibration, an opencv-based inspection tool was created and various verifications were performed. The purpose was to compare the performance of the two camera calibration algorithms by inputting images and coordinate points as input. (OpenCV vs. other companies) In 2021, Distortion Rational, Thin Prime Model interface were additionally updated, The 2022 Fisheye model interface was also updated. In general, normal calibration is sufficient to cover, but If you want a normal wide angle or more precision, you can use the Rational model, For ultra-wide-angle cameras, we recommend using the Fisheye model. Since the method of calculating the distortion index is different for each model, it must be used separately.

Python 100.00%
camera-calibration opencv pose-estimation stereo-camera rational-distortion fisheye-distortion stereo-rectification

stereo_camera_calibration_extension's Introduction

  • ๐Ÿ‘‹ Hi, Iโ€™m @yeolip
  • ๐Ÿ‘€ Iโ€™m interested in programming.

I'm in charge of stereo camera calibration on Driver Monitoring Camera team on 2019. main role is extracting stereo camera param, and match & verify it between camera product and DSM algo. I installed a camera inspection facility in the factory. I reduce number of images until similar performance for tack time and stabilize it.

I'm developed AVM view software engineer in ADAS ED on 2016. AVM(Around View Monitoring) assist customer's parking on driving. it use 4 fisheye camera and display 360 degree area from vehicle. I have interesting at Transparent Car. TC need recovery bindspot under vehicle for offroad, when driving. This concept need to vehicle's direction and velocity, and n-1 frame top view.

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