FREAK: Fast Retina Keypoint
École Polytechnique Fédérale de Lausanne
Abstract
A large number of vision applications rely on matching keypoints across images. The last decade featured an arms-race towards faster and more robust keypoints and association algorithms: Scale Invariant Feature Transform (SIFT)[17], Speed-up Robust Feature (SURF)[4], and more recently Binary Robust Invariant Scalable Keypoints (BRISK)[I6] to name a few. These days, the deployment of vision algorithms on smart phones and embedded devices with low memory and computation complexity has even upped the ante: the goal is to make descriptors faster to compute, more compact while remaining robust to scale, rotation and noise. To best address the current requirements, we propose a novel keypoint descriptor inspired by…
Citation impact
- FWCI
- 148.41
- Percentile
- 100%
- References
- 34
Authors
3- AAAlexandre AlahiCorresponding
École Polytechnique Fédérale de Lausanne
- ROR. Ortiz
École Polytechnique Fédérale de Lausanne
- PVPierre Vandergheynst
École Polytechnique Fédérale de Lausanne
Topics & keywords
- FREAK
- Scale-invariant feature transform
- Computer science
- Artificial intelligence
- Computer vision
- Computation
- Invariant (physics)
- Binary number