Robust Visual Robot Localization Across Seasons Using Network Flows
Authors: Tayyab Naseer, Luciano Spinello, Wolfram Burgard, Cyrill Stachniss
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We present extensive experimental evaluations under substantial seasonal changes. Our approach achieves accurate matching across seasons and outperforms existing state-of-the-art methods such as FABMAP2 and Seq SLAM. |
| Researcher Affiliation | Academia | Tayyab Naseer University of Freiburg naseer@cs.uni-freiburg.de Luciano Spinello University of Freiburg spinello@cs.uni-freiburg.de Wolfram Burgard University of Freiburg burgard@cs.uni-freiburg.de Cyrill Stachniss University of Bonn cyrill.stachniss@igg.uni-bonn.de |
| Pseudocode | No | The paper describes the algorithm in text form, but no structured pseudocode or algorithm blocks are provided. |
| Open Source Code | No | The paper refers to 'Open Seq SLAM implementation' and 'Open FABMAP2 implementation' for comparison, but does not provide concrete access to the source code for their own proposed methodology. |
| Open Datasets | No | For the evaluation, we recorded datasets by driving through a city with a camera-equipped car during summer and winter. The paper does not provide concrete access information for these datasets. |
| Dataset Splits | No | The paper uses its own collected datasets, with the 'database' and 'query' sets acting as the primary data divisions for matching experiments. However, it does not explicitly provide specific training/validation/test dataset splits (e.g., percentages, sample counts, or references to predefined splits) needed for reproduction in the typical machine learning sense. |
| Hardware Specification | No | Finally, our approach shows a comparable runtime to Seq SLAM. In all the experiments our approach takes between 2.1s and 3.7s on a regular PC using a single core. This description lacks specific hardware details such as CPU model, GPU, or memory. |
| Software Dependencies | No | The paper mentions using 'Open Seq SLAM implementation' and 'Open FABMAP2 implementation' for comparison but does not provide specific version numbers for any software dependencies used in their own method's implementation. |
| Experiment Setup | Yes | In our implementation, we use K = 4, which seems to be a sufficient value for typical city-like navigation scenarios. In case that the edge is connected to an hidden node, the weight is constant, w = W. We determined this parameter experimentally by using a precision-recall evaluation. |