Hand gesture recognition serves as a key for overcoming many difficulties and providing
convenience for human life. The ability of machines to understand human activities and their …

With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual
(RGB) sensing has become available for widespread use. The complementary nature of the …

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 …

This paper presents Soli, a new, robust, high-resolution, low-power, miniature gesture
sensing technology for human-computer interaction based on millimeter-wave radar. We …

Audio-visual speech recognition (AVSR) is one of the most promising solutions for reliable
speech recognition, particularly when audio is corrupted by noise. Additional visual …

The human hand moves in complex and high-dimensional ways, making estimation of 3D
hand pose configurations from images alone a challenging task. In this work we propose a …

We present a novel method for real-time continuous pose recovery of markerless complex
articulable objects from a single depth image. Our method consists of the following stages: a …

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 …

DeepPrior is a simple approach based on Deep Learning that predicts the joint 3D locations
of a hand given a depth map. Since its publication early 2015, it has been outperformed by …

In this paper, we develop a vision-based system that employs a combined RGB and depth
descriptor to classify hand gestures. The method is studied for a human-machine interface …