Related papers: GHAR: GeoPose-based Handheld Augmented Reality for…
Human Activity Recognition (HAR) has been a popular research field due to the widespread of devices with sensors and computational power (e.g., smartphones and smartwatches). Applications for HAR systems have been extensively researched in…
In this letter, we present a novel markerless 3D human motion capture (MoCap) system for unstructured, outdoor environments that uses a team of autonomous unmanned aerial vehicles (UAVs) with on-board RGB cameras and computation. Existing…
6DoF object pose estimation is fundamental to robotic grasp tasks. While recent learning-based methods achieve high accuracy, their computational demands hinder deployment on resource-constrained mobile platforms. In this work, we revisit…
We propose a method for annotating images of a hand manipulating an object with the 3D poses of both the hand and the object, together with a dataset created using this method. Our motivation is the current lack of annotated real images for…
The integration of haptics within Augmented Reality may help to deliver an enriched experience, while facilitating the performance of specific actions (e.g. repositioning or resizin ) that are still dependent on the user's skills. This…
Visual localization on standard-definition (SD) maps has emerged as a promising low-cost and scalable solution for autonomous driving. However, existing regression-based approaches often overlook inherent geometric priors, resulting in…
We present the HOH (Human-Object-Human) Handover Dataset, a large object count dataset with 136 objects, to accelerate data-driven research on handover studies, human-robot handover implementation, and artificial intelligence (AI) on…
Automated and accurate human activity recognition (HAR) using body-worn sensors enables practical and cost efficient remote monitoring of Activity of DailyLiving (ADL), which are shown to provide clinical insights across multiple…
Virtual content instability caused by device pose tracking error remains a prevalent issue in markerless augmented reality (AR), especially on smartphones and tablets. However, when examining environments which will host AR experiences, it…
Monocular 3D human pose estimation remains a challenging and ill-posed problem, particularly in real-time settings and unconstrained environments. While direct imageto-3D approaches require large annotated datasets and heavy models,…
Human Activity Recognition (HAR), based on machine and deep learning algorithms is considered one of the most promising technologies to monitor professional and daily life activities for different categories of people (e.g., athletes,…
The field of Augmented Reality (AR) based Human Robot Interaction (HRI) has progressed significantly since its inception more than two decades ago. With more advanced devices, particularly head-mounted displays (HMD), freely available…
Vision-based localization approaches now underpin newly emerging navigation pipelines for myriad use cases from robotics to assistive technologies. Compared to sensor-based solutions, vision-based localization does not require pre-installed…
We developed a ResNet-based human activity recognition (HAR) model with minimal overhead to detect gait versus non-gait activities and everyday activities (walking, running, stairs, standing, sitting, lying, sit-to-stand transitions). The…
3D Gaussian Splatting offers expressive scene reconstruction, modeling a broad range of visual, geometric, and semantic information. However, efficient real-time map reconstruction with data streamed from multiple robots and devices remains…
Together with the rapid development of the Internet of Things (IoT), human activity recognition (HAR) using wearable Inertial Measurement Units (IMUs) becomes a promising technology for many research areas. Recently, deep learning-based…
There has been a resurgence of applications focused on Human Activity Recognition (HAR) in smart homes, especially in the field of ambient intelligence and assisted living technologies. However, such applications present numerous…
Human activity recognition (HAR) from on-body sensors is a core functionality in many AI applications: from personal health, through sports and wellness to Industry 4.0. A key problem holding up progress in wearable sensor-based HAR,…
Hybrid rigid-soft robots combine the precision of rigid manipulators with the compliance and adaptability of soft arms, offering a promising approach for versatile grasping in unstructured environments. However, coordinating hybrid robots…
When considering sparse motion capture marker data, one typically struggles to balance its overfitting via a high dimensional blendshape system versus underfitting caused by smoothness constraints. With the current trend towards using more…