Towards automated video-based assessment of dystonia in dyskinetic cerebral palsy: A novel approach using markerless motion tracking and machine learning

Introduction: Video-based clinical rating plays an important role in assessing dystonia and monitoring the effect of treatment in dyskinetic cerebral palsy (CP). However, evaluation by clinicians is time-consuming, and the quality of rating is dependent on experience. The aim of the current study is to provide a proof-of-concept for a machine...

Visual Detection and Pose Estimation of Vulnerable Road Users for Automated Driving

This thesis addresses the topic of visual person detection and pose estimation. While these tasks are relevant for a broad range of applications, this thesis focuses on the domain of intelligent vehicles in urban traffic scenes. This domain is particularly interesting due to specific challenges related to visual perception from a moving vehicle....

Extrinsic Camera Calibration using Human-pose Estimations and Automatic Re-identification

Multi-pedestrian tracking in camera networks has gained enormous interest in the industry because of its applicability in travel-flow analysis, autonomous driving, and surveillance. Essential to tracking in camera networks is camera calibration and, in particular extrinsic camera calibration. Extrinsic camera calibration incorporates the 3D...

Automated Personnel Activities Observation in the Catheterization Laboratory

This thesis presents a method for personnel activities observation, i.e., 3D human pose estimation and tracking, in a Catheterization Laboratory(Cath Lab). We mount five cameras from different angles in the Cath Lab, where surgeons and assistants are in similar clothes while doing surgery. Accurate 3D human pose estimation is the cornerstone of...

VideoMuscle: Estimating human musculoskeletal model using neural networks from monocular video

We present the first deep learning approach to estimate the human skeletal system of the musculoskeletal model from monocular video. The current practice of musculoskeletal modeling relies on a motion capture system and OpenSim. The data is recorded in a restricted environment, and OpenSim workflow for musculoskeletal modeling is costly. Our...

One Pose Fits All: A novel kinematic approach to 3D human pose estimation

3D human pose estimation is a widely researched computer vision task that could be applied in scenarios such as virtual reality and human-robot interaction. With the lack of depth information, 3D estimation from monocular images is an inherently ambiguous problem. On top of that, unrealistic human poses have been overlooked in the majority of...

Visual Detection of Clinicians for Surgical Progress Recognition: Using the spatial distribution of medical personnel within the OR

Due to the ageing population and the availability of treatments, healthcare costs keep rising. Surgery is one of the big cost items in a hospital. Improvement of workflow, planning and process efficiency can aid in lowering the costs. Inefficiencies or the effect of improvements can only be detected through measurements. Therefore data is needed...

Towards Real-Time Human Pose Estimation For Mobile Device

Human pose estimation, a challenging computer vision task of estimating various human body joints' locations, has a wide range of applications such as pedestrian tracking for autonomous cars, baby monitoring, video surveillance, human action recognition, virtual reality, gaming, gait analysis, etc. A majority of the research on the development...

Tilting at windmills: Data augmentation for deep pose estimation does not help with occlusions

Occlusion degrades the performance of human pose estimation. In this paper, we introduce targeted keypoint and body part occlusion attacks. The effects of the attacks are systematically analyzed on the best-performing methods. In addition, we propose occlusion specific data augmentation techniques against keypoint and part attacks. Our extensive...

3D Human Pose Estimation: Using a Top-View Depth Camera

The onset of delirium, a disturbance in the mental activities of a patient, can be potentially detected by understanding activities within an Intensive Care Unit (ICU) room. Such activities can be extracted by estimating human pose via a visual capture of the scene. This work uses a top-view depth camera in an ICU room to estimate pose of the...

Flycon: Real-time environment-independent multi-view human pose estimation with aerial vehicles

We propose a real-time method for the infrastructure-free estimation of articulated human motion. The approach leverages a swarm of camer aequipped flying robots and jointly optimizes the swarm's and skeletal states, which include the 3D joint positions and a set of bones. Our method allows to track the motion of human subjects, for example...