Research Article

Efficient ConvNet Feature Extraction with Multiple RoI Pooling for Landmark-Based Visual Localization of Autonomous Vehicles

Figure 1

Sample examples of matched image pairs produced by a ConvNet landmark-based visual localization approach, which extracted ConvNet features by one variant of our proposed method, that is, MRoI-FastRCNN-AlexNet (see Section 5.1.2 for details). These images come from the testing datasets used in our experiments (see Section 5.1.1 for details). Six images on each row come from one dataset, and the three pairs illustrate images correctly matched by our method. The bounding boxes of the same color in each pair of matched images show the landmarks that have been matched. For clarity, we show only ten matched landmarks in each image. Best viewed in color.
(a) UACampus
(b) St. Lucia
(c) Nordland
(d) Mapillary