Direct use of the hand as an input device is an attractive method for providing natural human–
computer interaction (HCI). Currently, the only technology that satisfies the advanced …

This work addresses a novel and challenging problem of estimating the full 3D hand shape
and pose from a single RGB image. Most current methods in 3D hand analysis from …

We present an approach that uses a multi-camera system to train fine-grained detectors for
keypoints that are prone to occlusion, such as the joints of a hand. We call this procedure …

We present a system for real-time hand-tracking to drive virtual and augmented reality
(VR/AR) experiences. Using four fisheye monochrome cameras, our system generates …

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 …

Compared with depth-based 3D hand pose estimation, it is more challenging to infer 3D
hand pose from monocular RGB images, due to substantial depth ambiguity and the …

We extends the previous 2D cascaded object pose regression work [9] in two aspects so that
it works better for 3D articulated objects. Our first contribution is 3D pose-indexed features …

We present a realtime hand tracking system using a depth sensor. It tracks a fully articulated
hand under large viewpoints in realtime (25 FPS on a desktop without using a GPU) and …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

Pedestrian detection is a rapidly evolving area in computer vision with key applications in
intelligent vehicles, surveillance, and advanced robotics. The objective of this paper is to …