We address the highly challenging problem of real-time 3D hand tracking based on a
monocular RGB-only sequence. Our tracking method combines a convolutional neural …

We present a novel solution to the problem of 3D tracking of the articulated motion of human
hand (s), possibly in interaction with other objects. The vast majority of contemporary …

We present an approach for real-time, robust, and accurate hand pose estimation from
moving egocentric RGB-D cameras in cluttered real environments. Existing methods …

Tracking and reconstructing the 3D pose and geometry of two hands in interaction is a
challenging problem that has a high relevance for several human-computer interaction …

Tracking the articulated 3D motion of the hand has important applications, for example, in
human-computer interaction and teleoperation. We present a novel method that can capture …

Markerless tracking of hands and fingers is a promising enabler for human-computer
interaction. However, adoption has been limited because of tracking inaccuracies …

Real-time marker-less hand tracking is of increasing importance in human-computer
interaction. Robust and accurate tracking of arbitrary hand motion is a challenging problem …

Real-time simultaneous tracking of hands manipulating and interacting with external objects
has many potential applications in augmented reality, tangible computing, and wearable …

Real-time tracking of 3D hand pose in world space is a challenging problem and plays an
important role in VR interaction. Existing work in this space are limited to either producing …

We tackle the challenging task of estimating global 3D joint locations for both hands via only
monocular RGB input images. We propose a novel multi-stage convolutional neural network …