Open AccessJournal Article
Real-time tracking of multiple fingertips and gesture recognition for augmented desk interface systems
TLDR
A fast and robust method for tracking a user's hand and multiple fingertips and gesture recognition based on measured fingertip trajectories for augmented desk interface systems, which is particularly advantageous for human-computer interaction (HCI).About:
This article is published in IEEE Computer Graphics and Applications.The article was published on 2002-11-01 and is currently open access. It has received 170 citations till now. The article focuses on the topics: Gesture recognition & Desk.read more
Citations
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Journal ArticleDOI
Vision-based hand pose estimation: A review
TL;DR: A literature review on the second research direction, which aims to capture the real 3D motion of the hand, which is a very challenging problem in the context of HCI.
Proceedings ArticleDOI
Visual Tracking Using Depth Data
H. Nanda,Kikuo Fujimura +1 more
TL;DR: A method is presented for robust tracking in highly cluttered environments that makes effective use of 3D depth sensing technology, resulting in illumination-invariant tracking.
Proceedings ArticleDOI
A real time system for robust 3D voxel reconstruction of human motions
TL;DR: A multi-PC/camera system that can perform 3D reconstruction and ellipsoid fitting of moving humans in real time and using a simple and user-friendly interface, the user can display and observe, in realTime and from any view-point, the 3D models of the moving human body.
Proceedings ArticleDOI
Visual touchpad: a two-handed gestural input device
Shahzad Malik,Joe Laszlo +1 more
TL;DR: By segmenting the hand regions from the video images and then augmenting them transparently into a graphical interface, the Visual Touchpad provides a compelling direct manipulation experience without the need for more expensive tabletop displays or touch-screens, and with significantly less self-occlusion.
Journal ArticleDOI
Real-time hand tracking using a mean shift embedded particle filter
TL;DR: The proposed mean shift embedded particle filter (MSEPF) improves the sampling efficiency considerably and produces reliable tracking while effectively handling rapid motion and distraction with roughly 85% fewer particles.
References
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An introduction to hidden Markov models
TL;DR: The purpose of this tutorial paper is to give an introduction to the theory of Markov models, and to illustrate how they have been applied to problems in speech recognition.
Proceedings ArticleDOI
Recognizing human action in time-sequential images using hidden Markov model
Junji Yamato,J. Ohya,K. Ishii +2 more
TL;DR: The recognition rate is improved by increasing the number of people used to generate the training data, indicating the possibility of establishing a person-independent action recognizer.
Dissertation
Visual Recognition of American Sign Language Using Hidden Markov Models.
TL;DR: Using hidden Markov models (HMM's), an unobstrusive single view camera system is developed that can recognize hand gestures, namely, a subset of American Sign Language (ASL), achieving high recognition rates for full sentence ASL using only visual cues.
Proceedings ArticleDOI
Shadow gestures: 3D hand pose estimation using a single camera
Jakub Segen,Senthil Kumar +1 more
TL;DR: A system that uses a camera and a point light source to track a user's hand in three dimensions using depth cues obtained from projections of the hand and its shadow and computes the 3D position and orientation of two fingers.
Proceedings ArticleDOI
Fast tracking of hands and fingertips in infrared images for augmented desk interface
TL;DR: A fast and robust method for tracking positions of the centers and the fingertips of both right and left hands, which makes use of infrared camera images for reliable detection of a user's hands, and uses a template matching strategy for finding fingertips.