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Advanced Interactive Technologies

Acronymait
Homepagehttps://ait.ethz.ch
CountrySwitzerland
ZIP, City 
Address
Phone
TypeAcademy
Top-level organizationETH Zurich
Parent organizationInstitute for Intelligent Interactive Systems
Current organizationAdvanced Interactive Technologies
Memberships
  • Max Planck ETH Center for Learning Systems
  • ETH Competence Center - Competence Center for Rehabilitation Engineering and Science (RESC)


Open Opportunities

Human-centered View Synthesis

  • ETH Zurich
  • Advanced Interactive Technologies

In this project, we will propose a pipeline to generate novel view synthesis of multiple human performers. Please email the host for more details of the project.

  • Computer Vision
  • CLS Student Project (MPG ETH CLS), ETH Organization's Labels (ETHZ), IDEA League Student Grant (IDL), Master Thesis, Semester Project

Modeling 3D Human and Performance Capture

  • ETH Zurich
  • Advanced Interactive Technologies

Digital capture of human bodies is a rapidly growing research area in computer vision and computer graphics that puts scenarios such as life-like mixed-reality (MR) virtual-social interactions into reach. Therefore, we offer projects for modeling and capturing humans at the intersection of computer vision, computer graphics, and machine learning.

  • Computer Graphics, Computer Vision, Virtual Reality and Related Simulation
  • CLS Student Project (MPG ETH CLS), ETH Organization's Labels (ETHZ), Master Thesis, Semester Project

A machine learning approach to compensate the drift in IMU sensors

  • ETH Zurich
  • Advanced Interactive Technologies

Stable walking is one of the most fundamental dynamic movements to ensure the quality of lifestyle. However, the functionality of these systems deteriorates as people age, leading to a higher risk of falling. Fall-related injuries such as hip fracture, traumatic brain, and upper limb worsen the quality of lifestyle and put immense pressure on personal and social levels (1% of total annual healthcare expenditure; 25billion euros in Europe). Diagnostic tools to monitor movement deficits and abnormal motor patterns reliably and objectively during daily activities outside of clinical settings are mostly missing. Hence, the interpretation of data is limited. The advanced development of inertial measurement units (IMU) provided an alternative measuring paradigm. However, the characteristic of IMU causes drift in the system, which gets accumulated during calculation, thus giving wrong results. This study aims to develop a robust drift-compensation algorithm to derive spatial gait parameters.

  • Biomedical Engineering, Computer Vision, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Simulation and Modelling
  • CLS Student Project (MPG ETH CLS), ETH Organization's Labels (ETHZ), Internship, Master Thesis, Semester Project
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