Learning visual feature descriptors for dynamic lighting conditions
By Nicholas Carlevaris-Bianco, Ryan M. Eustice. 2014
79 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Roberto Arroyo
- Kazuya Takeda
- Pablo Fernández Alcantarilla
- Alexander Carballo
- Simon Stent
- Ekim Yurtsever
- Riccardo Gherardi
- Germán Ros
In Computer Vision and Pattern Recognition
- Ekim Yurtsever
- Alexander Carballo
- Jacob Lambert
- Roberto Arroyo
- Kazuya Takeda
- Pablo Fernández Alcantarilla
- Simon Stent
- Riccardo Gherardi
Citations in the corpus
- A Survey of Autonomous Driving: Common Practices and Emerging Technologies (2019, background): “Both attempting to extract lighting invariant features [149] and assessing the quality of features [150] have been proposed.”
- Visual Place Recognition: A Survey (2016, unknown): “Using webcam footage, Carlevaris-Bianco and Eustice [213]”
- Street-view change detection with deconvolutional networks (2016, background): “Approaches such as [4] to train features to match across dynamic lighting conditions could further improve the registration in challenging scenarios.”