Model-based 3D tracking of an articulated hand from single depth images
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Summary
This paper presents a novel solution to the problem of tracking the 3D position, orientation and full articulation of a human hand from single depth images and chooses the model-based approach and treats the tracking task as an optimization problem.
- Published
- 2013-09-01
- Cited by
- 1
- References
- 27
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:4980472
References
- Data glove integration with 3D virtual environments
- Human motion tracking for rehabilitation - A survey
- Automatic reconstruction of 3D human motion pose from uncalibrated monocular video sequences based on markerless human motion tracking
- Real-time human pose recognition in parts from single depth images
- Efficient model-based 3D tracking of hand articulations using Kinect
- Model-based hand tracking with texture, shading and self-occlusions
- A Framework for 3D Model-Based Visual Tracking Using a GPU-Accelerated Particle Filter
- Real-time hand-tracking with a color glove
- Particle swarm optimization
- Pose estimation and tracking using multivariate regression
- Visual Hand Tracking Using Nonparametric Belief Propagation
- Human Motion Tracking by Temporal-Spatial Local Gaussian Process Experts
- Tracking the articulated motion of two strongly interacting hands
- 3D hand pose reconstruction using specialized mappings
- Monocular real-time 3D articulated hand pose estimation
- Vision-based hand pose estimation: A review
- Defining a Standard for Particle Swarm Optimization
- 3D Human Motion Tracking using Manifold Learning
- Estimating 3D hand pose from a cluttered image
- Model-based 3D tracking of an articulated hand
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