Comparing image-based localization methods

This paper compares alternative approaches to pose estimation using visual cues from the environment. We examine approaches that derive pose estimates from global image properties, such as principal components analysis (PCA) versus from local image properties, commonly referred to as landmarks. We also consider the failure-modes of the different methods. Our work is validated with experimental results.

Authors

• Robert Sim Microsoft
• Gregory Dudek McGill University Samsung AI Center Montreal Mila - Quebec AI Institute

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