Selection of features and evaluation of visual measurements for 3-D robotic visual tracking
- 30 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 86 (21589860) , 320-325
- https://doi.org/10.1109/isic.1993.397693
Abstract
An overview is presented of the vision techniques that are used in order to automatically select features, measure features' displacements, and evaluate measurements during 3-D robotic visual tracking. The most robust technique proves to be the sum-of-squared differences (SSD) optical flow technique. Several techniques for the evaluation of the measurements are presented. These techniques can also be used for the selection of features for tracking in conjunction with several numerical criteria that guarantee the robustness of the servoing. The results from the application of these techniques to real images are discussed.Keywords
This publication has 8 references indexed in Scilit:
- Visual tracking of a moving target by a camera mounted on a robot: a combination of control and visionIEEE Transactions on Robotics and Automation, 1993
- Adaptive Robotic Visual TrackingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1991
- Weighted selection of image features for resolved rate visual feedback controlIEEE Transactions on Robotics and Automation, 1991
- Kalman filter-based algorithms for estimating depth from image sequencesInternational Journal of Computer Vision, 1989
- Spatiotemporal energy models for the perception of motionJournal of the Optical Society of America A, 1985
- Estimating three-dimensional motion parameters of a rigid planar patchIEEE Transactions on Acoustics, Speech, and Signal Processing, 1981
- Determining optical flowArtificial Intelligence, 1981
- The Interpretation of Visual MotionPublished by MIT Press ,1979