In this paper we introduce a large-scale hand pose dataset, collected using a novel capture
method. Existing datasets are either generated synthetically or captured using depth …

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 …

Human activity recognition (HAR) systems attempt to automatically identify and analyze
human activities using acquired information from various types of sensors. Although several …

Estimating hand-object manipulations is essential for in-terpreting and imitating human
actions. Previous work has made significant progress towards reconstruction of hand poses …

We present in this work the first end-to-end deep learning based method that predicts both
3D hand shape and pose from RGB images in the wild. Our network consists of the …

Estimating the 3D pose of a hand is an essential part of human-computer interaction.
Estimating 3D pose using depth or multi-view sensors has become easier with recent …

As computers become more pervasive in society, facilitating natural human–computer
interaction (HCI) will have a positive impact on their use. Hence, there has been growing …

Humans move their hands and bodies together to communicate and solve tasks. Capturing
and replicating such coordinated activity is critical for virtual characters that behave …

We present a new real-time hand tracking system based on a single depth camera. The
system can accurately reconstruct complex hand poses across a variety of subjects. It also …

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 …