66 citations · 158 across the 15 of their papers we have counts for
15 papers
Do predictability factors towards signing avatars hold across cultures?
Abdelhadi Soudi, Manal El Hakkaoui, Kristof Van Laerhoven
Avatar technology can offer accessibility possibilities and improve the Deaf-and-Hard of Hearing sign language users access to communication, education and services, such as the he…
Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition using Wrist-Worn Inertial Sensors
Alexander Hoelzemann, Julia Lee Romero, Marius Bock +2
We present a benchmark dataset for evaluating physical human activity recognition methods from wrist-worn sensors, for the specific setting of basketball training, drills, and game…
A Matter of Annotation: An Empirical Study on In Situ and Self-Recall Activity Annotations from Wearable Sensors
Alexander Hoelzemann, Kristof Van Laerhoven
Research into the detection of human activities from wearable sensors is a highly active field, benefiting numerous applications, from ambulatory monitoring of healthcare patients…
WEAR: An Outdoor Sports Dataset for Wearable and Egocentric Activity Recognition
Marius Bock, Hilde Kuehne, Kristof Van Laerhoven +1
Research has shown the complementarity of camera- and inertial-based data for modeling human activities, yet datasets with both egocentric video and inertial-based sensor data rema…
An Embedded and Real-Time Pupil Detection Pipeline
Ankur Raj, Diwas Bhattarai, Kristof Van Laerhoven
Wearable pupil detection systems often separate the analysis of the captured wearer's eye images for wirelessly-tethered back-end systems. We argue in this paper that investigating…
Using Multivariate Linear Regression for Biochemical Oxygen Demand Prediction in Waste Water
Isaiah K. Mutai, Kristof Van Laerhoven, Nancy W. Karuri +1
There exist opportunities for Multivariate Linear Regression (MLR) in the prediction of Biochemical Oxygen Demand (BOD) in waste water, using the diverse water quality parameters a…
Tutorial on Deep Learning for Human Activity Recognition
Marius Bock, Alexander Hoelzemann, Michael Moeller +1
Activity recognition systems that are capable of estimating human activities from wearable inertial sensors have come a long way in the past decades. Not only have state-of-the-art…
Detecting Handwritten Mathematical Terms with Sensor Based Data
Lukas Wegmeth, Alexander Hoelzemann, Kristof Van Laerhoven
In this work we propose a solution to the UbiComp 2021 Challenge by Stabilo in which handwritten mathematical terms are supposed to be automatically classified based on time series…
Transformer Networks for Data Augmentation of Human Physical Activity Recognition
Sandeep Ramachandra, Alexander Hoelzemann, Kristof Van Laerhoven
Data augmentation is a widely used technique in classification to increase data used in training. It improves generalization and reduces amount of annotated human activity data nee…
Improving Deep Learning for HAR with shallow LSTMs
Marius Bock, Alexander Hoelzemann, Michael Moeller +1
Recent studies in Human Activity Recognition (HAR) have shown that Deep Learning methods are able to outperform classical Machine Learning algorithms. One popular Deep Learning arc…
Toward Fault Detection in Industrial Welding Processes with Deep Learning and Data Augmentation
Jibinraj Antony, Florian Schlather, Georgij Safronov +2
With the rise of deep learning models in the field of computer vision, new possibilities for their application in industrial processes proves to return great benefits. Nevertheless…
On-site Online Feature Selection for Classification of Switchgear Actuations
Christina Nicolaou, Ahmad Mansour, Kristof Van Laerhoven
As connected sensors continue to evolve, interest in low-voltage monitoring solutions is increasing. This also applies in the area of switchgear monitoring, where the detection of…
A Multi-Media Exchange Format for Time-Series Dataset Curation
Philipp M. Scholl, Benjamin Völker, Bernd Becker +1
Exchanging data as character-separated values (CSV) is slow, cumbersome and error-prone. Especially for time-series data, which is common in Activity Recognition, synchronizing sev…
Wearable affect and stress recognition: A review
Philip Schmidt, Attila Reiss, Robert Duerichen +1
Affect recognition aims to detect a person's affective state based on observables, with the goal to e.g. provide reasoning for decision making or support mental wellbeing. Recently…
An Automated System for Discovering Neighborhood Patterns in Ego Networks
Syed Agha Muhammad, Kristof Van Laerhoven
Generally, social network analysis has often focused on the topology of the network without considering the characteristics of individuals involved in them. Less attention is given…