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Hire Kim N. - Computer Vision Engineer

Principal Computer Vision Engineer

33+ years
san mateo, california, united states
Oppo

About kim

A University of California PhD with concentration in image processing, computer vision, and machine learning. He has over 20 years of industrial experiences with publications and patents, which are highly cited and adapted by major institutions. He is especially skilled at developing robust algorithms that can be used in real-life systems. During early research years in the university, he developed innovative machine learning architecture that directly incorporated human knowledge with Fuzzy Logic and then refined through Neural Networks for non-linear control systems and autonomous robotic navigation. In STMicroelectronics, he developed 3D virtual view synthesis system that was robust to the depth inaccuracies from multiple wide-baseline stereovision. In JVC, he developed professional display calibration software that helped JVC venture into high-end lucrative commercial & fighter flight simulation markets, which generated hundreds of millions of dollars of new annual revenue. In Konica Minolta, he developed image stitching algorithm that rivaled the then state-of-the-art Adobe Photoshop CS6; the stitching algorithm was deployed for HDR imaging and panoramic imaging. In Nod, he developed visual-inertial motion tracking algorithm that enabled the world’s first mobile 6 Degrees-of-Freedom controllers to move in super-fast motion with high accuracy, low jitter, low latency, and instant pose re-acquisitions that was robust to the camera lens distortion, image sensor noises, fused LED blobs, extraneous environmental lighting, occlusions, unreliable IMU rates and IMU drifts; the algorithm tracked well even when the head pose wasn't piped through the camera-IMU system. He also contributed to the advancement of autonomous driving vehicles. At Xpeng, he developed lane detection and classification with deep learning networks; Lane line Stabilization with Kalman Filter; Severe Weather Classification with deep learning networks; Intelligent High Beam Control Development and integrated into the vehicle’s software stack. He further applied his algorithmic R&D and software coding skills at OPPO, where he filed 10 patents and publication. He developed innovative NIR + RGB sensor fusion that could see through fog and haze. He also productized a number of deep learning systems, such as 3D Photos, Image to Video Generation, Video Bokeh, running efficiently on cell phones. He is passionate for exploring new technological areas; he is ready to apply his AI skills in making autonomous driving & humanoid and many more deep learning systems a reality.

Key Skills

cc++computer visionimage processingmachine learningmatlabneural networksopencvpattern recognition

Experience

Principal Computer Vision Engineer

Current

Oppo

Developed, Patented, and Published Image Fusion Algorithms for Near-Infrared and color images that can see through fog and haze. Images from different sensor modalities were registered & fused into high-dynamic range natural color images. This can be beneficial for autonomous navigation in severe weather. Developed, Patented, and Productized 3D Photo Algorithm that allowed virtual look around from a single input image. The entire pipeline was heavily optimized and able to operate realtime on a cellphone. 3D were estimated and the occluded background were in-painted with deep learning networks. Developed and Productized Person Segmentation Deep Learning Network that also separated out the persons’ handheld objects automatically. Developed and Productized Video Bokeh Algorithm that handled multiple persons at different depth levels. 3D were estimated using Transformer deep learning networks. Developed Image to Video Generative AI Algorithm with Stable Diffusion. Given an input image, a short animated video of that input scene was generated. Surveyed 360-degree 3D Estimation Algorithms

Senior Staff Computer Vision Engineer

Xpeng

* Developed Computer Vision & Machine Learning Algorithms for Autonomous Self-Driving Vehicles: Lane Detection and classification with deep learning networks * Lane line Stabilization with Kalman Filter * Severe Weather Classification with deep learning networks * Intelligent High Beam Control Development and integrated into the vehicle’s software stack.

Senior Computer Vision Engineer

Nod.ai

Developed Visual-Inertial Motion Tracking Algorithm that enabled the world’s first mobile 6 Degrees-of-Freedom controllers to move in super-fast motion with high accuracy, low jitter, low latency, and instant pose re-acquisitions that was robust to the camera lens distortion, image sensor noises, fused LED blobs, extraneous environmental lightings, occlusions, unreliable IMU rates and IMU drifts; the algorithm tracked well even when the head pose wasn't piped through the camera-IMU system. See the demo in https://www.youtube.com/watch?v=_CyR_bDMLMI. Developed Data Collection and Annotation System for Training Hand Tracking with Deep Learning. Participated in Initial Discussions of Visual SLAM Development.

Education

Uc San Diego

Doctor Of Philosophy

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Common Questions

What is kim's expertise?

kim specializes in Computer Vision Engineer, with expertise in c, c++, computer vision, image processing, machine learning.

Where is kim located?

kim is based in san mateo, california, united states.

How much experience does kim have?

kim has 33+ years of professional experience.

How can I contact kim?

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