Speech-Enabled Augmented Reality Supporting Mobile Industrial Maintenance
IEEE Pervasive Computing
Fully Automated and Stable Registration for Augmented Reality Applications
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
Robust Visual Tracking for Non-Instrumented Augmented Reality
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
Model-Based Tracking with Stereovision for AR
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
Industrial Augmented Reality(IAR): Challenges in Design and Commercialization of Killer Apps
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
Handling Uncertain Sensor Data in Vision-Based Camera Tracking
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
Combining Edge and Texture Information for Real-Time Accurate 3D Camera Tracking
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
Automated Initialization for Marker-Less Tracking: A Sensor Fusion Approach
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
A Marker Calibration Method Utilizing A Priori Knowledge on Marker Arrangement
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
Scene Modelling, Recognition and Tracking with Invariant Image Features
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
Virtual and augmented reality support for discrete manufacturing system simulation
Computers in Industry - Special issue: The digital factory: an instrument of the present and the future
Tracking points using projective reconstruction for augmented reality
GRAPHITE '05 Proceedings of the 3rd international conference on Computer graphics and interactive techniques in Australasia and South East Asia
A Balanced Approach to 3D Tracking from Image Streams
ISMAR '05 Proceedings of the 4th IEEE/ACM International Symposium on Mixed and Augmented Reality
Calibration Errors in Augmented Reality: A Practical Study
ISMAR '05 Proceedings of the 4th IEEE/ACM International Symposium on Mixed and Augmented Reality
Real-Time Camera Tracking for Mobile Devices: The VisiTrack System
Real-Time Systems
Registration Using Natural Features for Augmented Reality Systems
IEEE Transactions on Visualization and Computer Graphics
Proceedings of the 2005 international conference on Augmented tele-existence
Texture overlay onto deformable surface for virtual clothing
Proceedings of the 2005 international conference on Augmented tele-existence
A vision-based AR registration method utilizing edges and vertices of 3D model
Proceedings of the 2005 international conference on Augmented tele-existence
Monocular model-based 3D tracking of rigid objects
Foundations and Trends® in Computer Graphics and Vision
Design experiences of multimodal mixed reality interfaces
SIGDOC '07 Proceedings of the 25th annual ACM international conference on Design of communication
Online camera pose estimation in partially known and dynamic scenes
ISMAR '06 Proceedings of the 5th IEEE and ACM International Symposium on Mixed and Augmented Reality
A mobile markerless AR system for maintenance and repair
ISMAR '06 Proceedings of the 5th IEEE and ACM International Symposium on Mixed and Augmented Reality
Parallel Tracking and Mapping for Small AR Workspaces
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Automatic Reconstruction of Wide-Area Fiducial Marker Models
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Real-Time Tracking Error Estimation for Augmented Reality for Registration with Linecode Markers
IEICE - Transactions on Information and Systems
Multiple planes based registration using 3D Projective Space for Augmented Reality
Image and Vision Computing
Trends in augmented reality tracking, interaction and display: A review of ten years of ISMAR
ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
Virtual and augmented reality support for discrete manufacturing system simulation
Computers in Industry - Special issue: The digital factory: an instrument of the present and the future
Feature management for efficient camera tracking
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Fusion of 3d and appearance models for fast object detection and pose estimation
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
AR baseball presentation system with integrating multiple planar markers
ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
An efficient 3d registration method using markerless image in AR-Based CNC machining simulation
ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
A computational model for the integration of linked data in mobile augmented reality applications
Proceedings of the 8th International Conference on Semantic Systems
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Estimating the pose of a camera (virtual or real) in which some augmentation takes place is one of the most important parts of an augmented reality (AR) system. Availability of powerful processors and fast frame grabber shave made vision-based trackers commonly used due to their accuracy as well as flexibility and ease of use. Current vision-based trackers are based on tracking of markers. The use of markers increases robustness and reduces computational requirements. However, their use can be very complicated, as they require certain maintenance. Direct use of scene features for tracking, therefore, is desirable. To this end, we describe a general system that tracks the position and orientation of a camera observing a scene without any visual markers. Our method is base don a two-stage process. In the first stage, a set of features is learned with the help of an external tracking system while in action. The second stage uses these learned features for camera tracking when the system in thefirst stage decides that it is possible to do so. The system is very general so that it can employ any available feature tracking and pose estimation system for learning and tracking. We experimentally demonstrate the viability of the method in real-life examples.