Research team

Expertise

PhD in optical metrology (e.g. fringe projecting profilometry). Projects on thermography, time-of-flight imaging, RGB and hyperspectral imaging for several applications such as sealing control, material characterization, quality control, skeleton tracking, blood flow detection, etc.

Industrial computer vision services enabled by a generic Python camera toolbox. 01/09/2023 - 31/08/2024

Abstract

The goal of this Service Platform project is firstly to provide feasibility and data acquisition services to companies interested in utilising cutting-edge camera technologies (like high-speed, thermal and hyperspectral cameras). Our services will assist companies in making better, well-informed decisions and offer valuable perspectives on utilising and integrating these technologies into their solutions. Secondly, we will offer easy-to-use software tools needed to integrate cameras quickly and in a standardised way into their customised implementations. Our user-friendly generic camera acquisition toolbox for Python (GenPyCam) will facilitate camera deployment (also on embedded and virtualised systems). In this way, image processing companies will be able to solve problems they could not tackle before, their capabilities in terms of camera types will increase, and their camera software implementation cost will decrease significantly.

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Project website

Project type(s)

  • Research Project

D Thermal imaging of people using statistical shape models. 01/10/2020 - 30/09/2022

Abstract

In this project, we will develop an easy to use method to monitor the thermal condition of a person as a function of time, with potential applications entailed in physical treatment or a sports activity. The method employs amongst others thermal imaging. To that end, we create a virtual 3D model of the person of interest. The proposed technique will enable the development of a flexible and mobile measurement system, which can be used in labs, hospitals, rehabilitation centers, sports training facilities, etc.

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  • Research Project

4D scanner for Accelerating Advanced motion Analysis and Application 01/05/2020 - 30/04/2024

Abstract

The human body is a complex bio-mechanical system that exhibits many variations in geometry and movements. Advancements in 3D scanning and 3D modeling allow to construct precise and high-resolution models of the human body. Such a 3D model often contains more than 2GB of information such that recording, processing, transmission and data storage is labor and time intensive. In this project we acquire a 3D body scanner that captures the human body shape in high precision and with virtually no effort. The equipment will allow to register the human body with an accuracy of 1mm and up, at a frame rate of 10 3D scans per second. This so called 4D scanner (3D + time) constitutes the core of our 4D center of expertise, in which the research groups Product Development, MOVANT, Vision Lab, EVECO and Op3Mech together with Center for Health and Technology (CHaT) have joined forces in a complementary collaboration with the aim to use dynamical models of the human body for the development of new products with improved comfort and functionality, to design fundamentally new products with important applications in health care, and to improve our understanding of the evolutionary history of the human body. The combination of academic and industrial expertise of Kinesiology with Product Development and virtual modeling and simulations makes the center unique in the world. The consortium will tackle open design problems with applications for mass customization (3D printing) and wearables.

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  • Research Project

Validation of markerless body tracking for real world gait analysis. 01/07/2018 - 31/12/2019

Abstract

Markerless motion tracking became very popular and common since the introduction of the Microsoft Kinect in 2010 in both the gaming community and industry. To use markerless motion tracking in the field of medical rehabilitation, a higher accuracy and reliability is needed. To achieve this goal, we will combine a 2-D skeleton detection algorithm with the data from multiple 3-D cameras. The developed procedure will be validated with the marker-based Vicon system of the M²OCEAN lab and calibrated 3D body scans of subjects in static position. Afterwards, the technique will be implemented on a treadmill to evaluate the gait of a person. To simulate real world gait information, subjects will wear virtual reality glasses. This virtual environment stimulates the brain and influences the gait of a person, which results in extra information compared to stand alone treadmill walking.

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  • Research Project

Thermal hyperspectral material characterization for Art Conservation based on hypercubes. 01/07/2016 - 31/12/2017

Abstract

In the study of historical paintings and more specifically as a preparation for restoration activities of such artefacts, it is of great relevance to investigate which materials and degradation products are present and how these are distributed at or below the painting surface. Commonly used non-destructive in situ methods such as X-ray fluorescence (XRF) and X-ray diffraction (XRD), are only used for spot analyses and require several minutes to record a spectrum from a single sample position, resulting in long scanning times required to record the data hypercubes. As an alternative, thermography inspection, as a non-contact and non-destructive technique is used for material parameter identification but also for art inspection as it is possible to differentiate chemical compounds. Therefore the goal of this research proposal is to improve non-invasive macroscopic material characterization of flat objects, both from an industrial and cultural heritage context, by augmenting existing elemental imaging technology with more species specific imaging of organic and inorganic compounds and this by combining the established X-ray based approaches with IR thermography and hyperspectral (HS) images. A combined X-ray, IR thermography and HS technique eliminates the disadvantages of these techniques and results in a faster measurement and material identification technique with respect to measurement time but also accuracy of the material parameter identification.

Researcher(s)

Research team(s)

Project type(s)

  • Research Project