Real-Time Visual Tracking of Complex Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hyperplane Approximation for Template Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Stable Real-Time 3D Tracking Using Online and Offline Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Fusing Points and Lines for High Performance Tracking
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Monocular model-based 3D tracking of rigid objects
Foundations and Trends® in Computer Graphics and Vision
Pose tracking from natural features on mobile phones
ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
Object recognition and full pose registration from a single image for robotic manipulation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Object recognition and pose estimation using color cooccurrence histograms and geometric modeling
Image and Vision Computing
Point matching as a classification problem for fast and robust object pose estimation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Benchmarking template-based tracking algorithms
Virtual Reality - Special Issue on Augmented Reality
Efficient Homography-Based Tracking and 3-D Reconstruction for Single-Viewpoint Sensors
IEEE Transactions on Robotics
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This paper presents a hybrid approach by fusing template and keypoint based tracking to track pose of planar textured targets with large interframe displacement. The fusion is made such that it adds to accuracy and convergence of template based tracking. The approach is not only robust against illumination changes and partial occlusion, but also free from offline pose learning and prior knowledge about background which makes it flexible to adapt change in scene.