This paper presents a thorough performance analysis of several variants of the feature-based visual navigation system that uses RGB-D data to estimate in real-time the trajectory of a freely moving sensor. The evaluation focuses on the advantages and problems that are associated with choosing a particular structure of the sensor-tracking front-end, employing particular feature detectors/descriptors, and optimizing the resulting trajectory treated as a graph of sensor poses. Moreover, a novel yet simple graph pruning algorithm is introduced, which enables to remove spurious edges from the pose-graph. The experimental evaluation is performed on two publicly available RGB-D data sets to ensure that our results are scientifically verifiable.
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