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Position: Master Thesis „Structure-based real-time 3D pose tracking”
Institution: Austrian Institute of Technology GmbH
Location: Wien, Austria
Duties: Based on our recent research results one of your tasks is to extend our algorithmic pipeline to introduce temporal propagation and structure-based validation of pose estimation under varying views and partial occlusions; Moreover, you will investigate limits of structure-based pose tracking starting with simple then increasingly complex 3D geometric shapes; You will learn to use graph-based representations to track structures with attributes of self-occluding (or mutually occluding) objects in real-time
Requirements: Ongoing master’s studies in the field of computer science, software engineering, information and computer engineering, mathematics, robotics or similar; Knowledge of fundamental Computer Vision and/or Machine Learning concepts; Experience in Python, preferably also in PyTorch; Interest in applied aspects of modern machine learning and robot vision; Good knowledge of verbal and written English
   
Text: We are Austria’s largest Research and Technology Organization and an international player in the research areas that we cover. This makes us a leading development partner for industry and a top employer in the scientific community. Our Center for Vision, Automation & Control in Vienna invites applications for a: Master Thesis „Structure-based real-time 3D pose tracking” Assistive & Autonomous Systems Our team’s expertise is sensor and algorithm development for assistance systems of vehicles and machines that recognize the environment in 3D. Automated robotic systems need abilities to recognize objects, object parts and their 3D spatial pose. We cooperate with national and international research organizations and companies. Based on our recent research results one of your tasks is to extend our algorithmic pipeline to introduce temporal propagation and structure-based validation of pose estimation under varying views and partial occlusions. Moreover, you will investigate limits of structure-based pose tracking starting with simple then increasingly complex 3D geometric shapes. You will learn to use graph-based representations to track structures with attributes of self-occluding (or mutually occluding) objects in real-time. You will build a structural tracking framework for a wide range of geometric structures. You will validate this framework on a set of increasingly complex practical scenarios and finalize it as a proof of concept demonstrator system in Python/PyTorch. You will evaluate, and document test runs in pre-defined scenarios and publish the results at a robotics/computer vision conference or journal. Your qualifications as an Ingenious Partner* : Ongoing master’s studies in the field of computer science, software engineering, information and computer engineering, mathematics, robotics or similar Knowledge of fundamental Computer Vision and/or Machine Learning concepts Experience in Python, preferably also in PyTorch Interest in applied aspects of modern machine learning and robot vision Good knowledge of verbal and written English What to expect: EUR 779,25,- gross per month for 20 hours/week based on the collective agreement. There will be additional company benefits. You will be part of our international Young AIT network. As a research institution, we are familiar with the supervision and execution of master theses and we are looking forward to supporting you accordingly. At AIT, the promotion of women is important to us - that's why we are especially looking forward to applications from female students! Please submit your application documents including your CV, motivational letter and certificates online. Tomorrow Today - with You? Apply now! Apply online now Back to job listing Print × Close Interested? Drag your CV here or upload it to create a new profile. Upload your CV ;
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