Computer Vision
[Closed]
Work description
Human pose estimation involves understanding the complex positioning and orientation of an individual's body joints within a single frame or a sequence of images. Beyond its technical aspects, this field has significant impact in different areas such as healthcare, playing a crucial role in interpreting human movement. The precision achieved in human pose estimation has broad applications, from recognizing gestures to advancing rehabilitation and physical therapy. Within the healthcare domain, the adoption of markerless vision-based methodologies minimizes interference with patients while enabling the comprehensive capture of a diverse array of exercises. Therefore, the main goals are: i) select which vision sensors are more appropriate for the considered case study (Kinect, OAK-D, Intel® RealSense, among others); ii) choose one or two state-of-the-art methods for pose estimation; iii) evaluate and compare the pose.
Academic Qualifications
Degree in Bioengineering, or related areas.
Minimum profile required
Python computer programming. The candidate must be enrolled in a Master's degree in Bioengineering, or related areas.
Preference factors
Knowledge or experience in image/video processing, 3D data manipulation, machine learning, and deep learning methods
Application Period
Since 21 Dec 2023 to 05 Jan 2024
[Closed]
Centre
Robotics in Industry and Intelligent Systems