Year: 2013
Type: conference-paper
Abstract: Natural human computer interaction motivates hand tracking research, preferably without requiring the user to wear special hardware or markers. Ideally, a hand tracking solution would provide not only points of interest, but the full state of an entire hand. [Oikonomidis et al. 2011] demonstrated a particle swarm optimization that tracked a 3D skeletal hand model from a single depth camera, albeit using significant computing resources. In contrast, we track the hand from a single depth camera using an efficient physical simulation, which incrementally updates a model's fit and explores alternative candidate poses based on a variety of heuristics. Our approach enables real-time, robust 3D skeletal tracking of a user's hand, while utilizing a single x86 CPU core for processing.
Authors: Stan Melax, Leonid Keselman, Sterling Orsten
Institution: Intel (United States)
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: Intel Corporation
OpenAlex ID: W1633557510