Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Using vision, acoustics, and natural language for disambiguation
Proceedings of the ACM/IEEE international conference on Human-robot interaction
Mobile, dexterous, social robots for mobile manipulation and human-robot interaction
ACM SIGGRAPH 2008 new tech demos
Efficient illumination independent appearance-based face tracking
Image and Vision Computing
Adaptive view-based appearance models
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A Minimalistic Approach to Appearance-Based Visual SLAM
IEEE Transactions on Robotics
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Tracking people and objects is an enabling technology for many robotic applications. From human-robot-interaction to SLAM, robots must know what a scene contains and how it has changed, and is changing, before they can interact with their environment. In this paper, we focus on the tracking necessary to record the 3D position and pose of objects as they change in real time. We develop a tracking system that is capable of recovering object locations and angles at speeds in excess of 60 frames per second, making it possible to track people and objects undergoing rapid motion and acceleration. Results are demonstrated experimentally using real objects and people and compared against ground truth data.