Tracking and data association
Active shape models—their training and application
Computer Vision and Image Understanding
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Bundle Adjustment - A Modern Synthesis
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Drift-Free Real-Time Sequential Mosaicing
International Journal of Computer Vision
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 tree skeletal structures from point clouds
ACM SIGGRAPH Asia 2010 papers
Automated 3D Segmentation and Analysis of Cotton Plants
DICTA '11 Proceedings of the 2011 International Conference on Digital Image Computing: Techniques and Applications
iSAM2: Incremental smoothing and mapping using the Bayes tree
International Journal of Robotics Research
Classification of plant structures from uncalibrated image sequences
WACV '12 Proceedings of the 2012 IEEE Workshop on the Applications of Computer Vision
Optimising Light Source Positions to Minimise Illumination Variation for 3D Vision
3DIMPVT '12 Proceedings of the 2012 Second International Conference on 3D Imaging, Modeling, Processing, Visualization & Transmission
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This paper describes a framework for model-based 3D reconstruction of vines and trellising for a robot equipped with stereo cameras and structured light. In each frame, high-level 2D features, and a sparse set of 3D structured light points are found. Detected features are matched to 3D model components, and the g2o optimisation framework is used to estimate both the model's structure and the camera's trajectory. The system is demonstrated reconstructing the trellising present in images of vines, together with the camera's trajectory, over a 12m track consisting of 360 sets of frames. The estimated model is structurally correct and is almost complete, and the estimated trajectory drifts by just 4%. Future work will extend the framework to reconstruct the more complex structure of the vines.