Digital image analysis
Adaptive tracking and model registration across distinct aspects
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 1 - Volume 1
Monocular model-based 3D tracking of rigid objects
Foundations and Trends® in Computer Graphics and Vision
Real-time object tracking using bounded irregular pyramids
Pattern Recognition Letters
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
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
Pose tracking from natural features on mobile phones
ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
Multiple target detection and tracking with guaranteed framerates on mobile phones
ISMAR '09 Proceedings of the 2009 8th IEEE International Symposium on Mixed and Augmented Reality
Fast Keypoint Recognition Using Random Ferns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Construction of combinatorial pyramids
GbRPR'03 Proceedings of the 4th IAPR international conference on Graph based representations in pattern recognition
Evaluation of Interest Point Detectors and Feature Descriptors for Visual Tracking
International Journal of Computer Vision
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Real-time 3D pose estimation from monocular image sequences is a challenging research topic. Although current methods are able to recover 3D pose, they are severely challenged by the computational cost. To address this problem, we propose a tracking and 3D pose estimation method supported by three main pillars: a pyramidal structure, an aspect graph and the checkpoints. Once initialized the systems performs a top-down tracking. At a high level it detects the position of the object and segments its time-space trajectory. This stage increases the stability and the robustness for the tracking process. Our main objective is the 3D pose estimation, the pose is estimated only in relevant events of the segmented trajectory, which reduces the computational effort required. In order to obtain the 3D pose estimation in the complete trajectory, an interpolation method, based on the aspect graph describing the structure of the object's surface, can be used to roughly estimate the poses between two relevant events. This early version of the method has been developed to work with a specific type of polyhedron with strong edges, texture and differentiated faces, a die.