8.0 - 10.0 years

0 Lacs

Pune, Maharashtra, India

On-site

Role Description ? Design and implement robust computer vision algorithms for object detection, recognition, tracking, and scene understanding Multi-View Geometry: Apply multi-view geometry techniques to develop 3D reconstruction, localization, and mapping solutions Classical Computer Vision: Utilize classical computer vision methods including feature extraction, image processing, and segmentation Collaboration: Work closely with cross-functional teams, including hardware engineers, software developers Research and Innovation: Stay updated with the latest advancements in computer vision and robotics, and apply innovative techniques to improve perception systems Skill Requirements PRIMARY SKILLS (MUST HAVE SKILLS): Experience with computer vision applications on monocular and stereo imaging Working knowledge of 3D localisation and mapping techniques on monocular and stereo imaging Understanding of video annotation, video analytics, 3D and Stereo capture and Visualisation Proficiency in multimodal image registration (CT-CT, CT-MRI, Fluro-Endo, 3D-3D, 2D-3D) Experience with image denoising and enhancement Strong understanding of camera models (e.g. pin-hole, fish-eye ) and camera calibration processes Proficient in multi-view geometry and 3D reconstruction techniques Strong knowledge of classical computer vision algorithms Proficient in programming languages such as Python/ C++/ MATLAB Experience with computer vision libraries (e.g., OpenCV, PCL) SECONDARY SKILLS: (GOOD TO HAVE) Experience in endoscopy imaging, image mosiacing, image fusion with ultrasound imaging. Working knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch) is a plus Strong problem-solving and analytical skills Excellent communication and teamwork abilities Ability to work in a fast-paced and dynamic environment Qualifications And Education Requirements Education: Bachelor&aposs , Master&aposs or PhD&aposs degree in Computer Science or related field Experience: Minimum of 8 years of experience in computer vision Show more Show less

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