Related papers: Three-dimensional hand guidance by midair haptic d…

The emergence of virtual reality has necessitated the generation of detailed and customizable 3D hand models for interaction in the virtual world. However, the current methods for 3D hand model generation are both expensive and cumbersome,…

Understanding how we grasp objects with our hands has important applications in areas like robotics and mixed reality. However, this challenging problem requires accurate modeling of the contact between hands and objects. To capture grasps,…

Humans process significantly more information through the sense of touch than through vision. Consequently, haptics for telemanipulation is poised to become essential in the coming years, as it offers operators an additional sensory channel…

Accuracy and speed are pivotal when typing. Mixed reality typing is typically performed by typing on a midair keyboard with your index fingers. This deprives users of both the tactile feedback available on physical devices and the ability…

Neurological conditions are a major source of movement disorders. Motion modelling and variability analysis have the potential to identify pathology but require profound data. We introduce a systematic dataset of 3D center-out task-space…

Hand guidance of robots has proven to be a useful tool both for programming trajectories and in kinesthetic teaching. However hand guidance is usually relegated to robots possessing joint-torque sensors (JTS). Here we propose to extend hand…

We tackle the novel problem of predicting 3D hand motion and contact maps (or Interaction Trajectories) given a single RGB view, action text, and a 3D contact point on the object as input. Our approach consists of (1) Interaction Codebook:…

Relocation of haptic feedback from the fingertips to the wrist has been considered as a way to enable haptic interaction with mixed reality virtual environments while leaving the fingers free for other tasks. We present a pair of wrist-worn…

This paper presents a new method for detecting and classifying a predefined set of hand gestures using a single transmitter and a single receiver utilizing a linearly frequency modulated ultrasonic signal. Gestures are identified based on…

In this paper, we strive to answer two questions: What is the current state of 3D hand pose estimation from depth images? And, what are the next challenges that need to be tackled? Following the successful Hands In the Million Challenge…

Optical see-through augmented reality (OST-AR) overlays digital targets and annotations on the physical world, offering promising guidance for hands-on tasks such as medical needle insertion or assembly. Recent work on OST-AR depth…

Tracking the full skeletal pose of the hands and fingers is a challenging problem that has a plethora of applications for user interaction. Existing techniques either require wearable hardware, add restrictions to user pose, or require…

Markerless tracking of hands and fingers is a promising enabler for human-computer interaction. However, adoption has been limited because of tracking inaccuracies, incomplete coverage of motions, low framerate, complex camera setups, and…

BACKGROUND: Learning to perform new movements is usually achieved by following visual demonstrations. Haptic guidance by a force feedback device is a recent and original technology which provides additional proprioceptive cues during…

Pseudo-haptics techniques are interesting alternatives for generating haptic perceptions, which entails the manipulation of haptic perception through the appropriate alteration of primarily visual feedback in response to body movements.…

In this paper, we present a method to manipulate unknown objects in-hand using tactile sensing without relying on a known object model. In many cases, vision-only approaches may not be feasible; for example, due to occlusion in cluttered…

Robotics has shown significant potential in assisting people with disabilities to enhance their independence and involvement in daily activities. Indeed, a societal long-term impact is expected in home-care assistance with the deployment of…

Human motion prediction is crucial for human-centric multimedia understanding and interacting. Current methods typically rely on ground truth human poses as observed input, which is not practical for real-world scenarios where only raw…

We tackle the problem of forecasting bimanual 3D hand motion & articulation from a single image in everyday settings. To address the lack of 3D hand annotations in diverse settings, we design an annotation pipeline consisting of a diffusion…

This paper proposes a vision-based framework for a 7-degree-of-freedom robotic manipulator, with the primary objective of facilitating its capacity to acquire information from human hand demonstrations for the execution of dexterous…