Robust Real-Time SLAM Using Multiresolution Descriptors

 

This work in collaboration with Denis Chekhlov, Mark Pupilli and Andrew Calway, uses SIFT-like descriptors within a coherent top-down framework.  The resulting system provides superior performance over previous methods in terms of robustness to erratic motion, camera shake, and the ability to recover from periods of measurement loss.

• Denis Chekhlov, Mark Pupilli, Walterio Mayol-Cuevas and Andrew Calway. Robust Real-Time Visual SLAM Using Scale Prediction and Exemplar Based Feature Description [PDF]. [VIDEO] In proceedings IEEE Computer Vision and Pattern Recognition CVPR, Minneapolis, Minnesota, USA. 2007.

• Denis Chekhlov, Mark Pupilli, Walterio Mayol-Cuevas and Andrew Calway. Real-Time and Robust Monocular SLAM Using Predictive Multi-resolution Descriptors [PDF]. To appear in LNCS proceedings of the 2nd International Symposium on Visual Computing, November 2006.