Object recognition by computer: the role of geometric constraints
Object recognition by computer: the role of geometric constraints
Robust model-based motion tracking through the integration of search and estimation
International Journal of Computer Vision
Active vision
3D object recognition using invariance
Artificial Intelligence - Special volume on computer vision
X Vision: a portable substrate for real-time vision applications
Computer Vision and Image Understanding
Indexing without Invariants in 3D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-Based Stereo-Tracking of Non-Polyhedral Objects for Automatic Disassembly Experiments
International Journal of Computer Vision - Special issue on image-based servoing
3D Real-Time Head Tracking Fusing Color Histograms and Stereovision
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Providing synthetic views for teleoperation using visual pose tracking in multiple cameras
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Computer Vision and Image Understanding
Motion and scene complexity for streaming video games
Proceedings of the 4th International Conference on Foundations of Digital Games
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In vision-based robotic systems the robust tracking of scene features is a key element of grasping, navigation and interpretation tasks. The stability of feature initialisation and tracking is strongly influenced by ambient conditions, like lighting and background, and their changes over time. This work presents how robustness can be increased especially in complex scenes by reacting to a measurement of the scene content. Element candidates are proposed, to indicate the scene complexity remaining after running a method. Local cue integration and global topological constraints are applied to select the best feature set. Experiments show in particular the success of the approach to disambiguate features in complex scenes.