With the rapid advances in mobile computing, handheld Augmented Reality draws increasing attention. Pose tracking of handheld devices is of fundamental importance to register virtual information with the real world and is still a crucial challenge. In this paper, we present a low-cost, accurate and robust approach combining fiducial tracking and inertial sensors for handheld pose tracking. Two LEDs are used as fiducial markers to indicate the position of the handheld device. They are detected by an adaptive thresholding method which is robust to illumination changes, and then tracked by a Kalman filter. By combining inclination information provided by the on-device accelerometer, 6 degree-of-freedom (DoF) pose is estimated. Handheld devices...
The focus of this thesis is on studying diverse techniques, methods and sensors for position and ori...
This thesis explores visual-inertial tracking for the application in Augmented Reality. Combining vi...
Most augmented reality solutions are based on computer vision techniques to detect and track objects...
With the rapid advances in mobile computing, handheld Augmented Reality draws increasing attention. ...
With the rapid advances in mobile computing, handheld Augmented Reality draws increasing attention. ...
With the rapid advances in mobile computing, handheld Augmented Reality draws increasing attention. ...
Tracking of a handheld device’s three-dimensional (3-D) position and orientation is fundamental to v...
Tracking of a handheld device’s three-dimensional (3-D) position and orientation is fundamental to v...
As the booming of mobile technologies, handheld Augmented Reality draws increasing attention. One cr...
This paper aims at robust and efficient pose tracking for augmented reality on modern smartphones. E...
Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight...
Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight...
Most augmented reality solutions are based on computer vision techniques to detect and track objects...
International audienceIn this paper, we present a robust fiducials tracking method for real time Aug...
The focus of this thesis is on studying diverse techniques, methods and sensors for position and ori...
The focus of this thesis is on studying diverse techniques, methods and sensors for position and ori...
This thesis explores visual-inertial tracking for the application in Augmented Reality. Combining vi...
Most augmented reality solutions are based on computer vision techniques to detect and track objects...
With the rapid advances in mobile computing, handheld Augmented Reality draws increasing attention. ...
With the rapid advances in mobile computing, handheld Augmented Reality draws increasing attention. ...
With the rapid advances in mobile computing, handheld Augmented Reality draws increasing attention. ...
Tracking of a handheld device’s three-dimensional (3-D) position and orientation is fundamental to v...
Tracking of a handheld device’s three-dimensional (3-D) position and orientation is fundamental to v...
As the booming of mobile technologies, handheld Augmented Reality draws increasing attention. One cr...
This paper aims at robust and efficient pose tracking for augmented reality on modern smartphones. E...
Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight...
Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight...
Most augmented reality solutions are based on computer vision techniques to detect and track objects...
International audienceIn this paper, we present a robust fiducials tracking method for real time Aug...
The focus of this thesis is on studying diverse techniques, methods and sensors for position and ori...
The focus of this thesis is on studying diverse techniques, methods and sensors for position and ori...
This thesis explores visual-inertial tracking for the application in Augmented Reality. Combining vi...
Most augmented reality solutions are based on computer vision techniques to detect and track objects...