Augmented reality is upending many industrial sectors by offering a new way to perceive the environment.
With its expertise in computer vision, pose estimation, and 3D visualization, the Immersive & Medical Technologies lab designs components and platforms to augment the experiences of professionals and strengthen their effectiveness, particularly through augmented reality and virtual reality, in fields like industry and health. Users are at the heart of its thinking and its work, from the definition of needs to the testing of developed technologies. In the field of health care, the lab works with its medical partners on key technologies like image processing and medical videos, connectivity, and interoperability.
03.08.2019
Camera relocalization is a common problem in several applications such as augmented reality or robot navigation. Especially, augmented reality requires fast, accurate and robust camera localization. However, it is still challenging to have a both real-time and accurate method. In this paper, we present our hybrid method combing machine learning approach and geometric approach for real-time camera…
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08.21.2018
The main objective of this work is to facilitate the identification, sharing and reasoning about cerebral tumors observations via the formalization of their semantic meanings in order to facilitate their exploitation in both the clinical practice and research. We have focused our analysis on the VASARI terminology as a proof of concept, but we are convinced that our work can be useful in other…
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10.04.2018
Imaging Biomarker Ontology (IBO): A Biomedical Ontology to Annotate and Share Imaging Biomarker Data
Imaging biomarkers refer to radiological measurements that characterize biological processes of imaged subjects and help clinicians particularly in the assessment of therapeutic responses and the early prediction of pathologies. Several imaging features (size of a lesion, volume of a tumor, blood perfusion in a specific anatomical region, anisotropic water diffusion in a particular tissue region,…
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01.07.2019
Accurate Sparse Feature Regression Forest Learning for Real-Time Camera Relocalization
Camera relocalization is needed in several applications such as augmented reality or robot navigation. However, it is still challenging to have a both real-time and accurate method. In this paper, we present our hybrid method combing machine learning approach and geometric approach for real-time camera relocalization from a single RGB image. We introduce our sparse feature regression forest to…
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