AlexandreAlahi

Contents

Home
Research Projects
Publications
Teaching
Data set
Source Code
CV
Media Coverage


Research fields

Computer Vision
Signal Processing
Machine learning
Robotics
Computational Neuroscience


Research Interests

Sparse approximation
Compressed-sensing
Inverse problems
Real-time vision
Bio-inspired vision
Large-scale vision
Big Visual data

 

 

FREAK: Fast Retina Keypoint: C/C++ code (integrated to openCV)

Gesture Recognition The last decade featured an arms-race towards faster and more robust keypoints and association algorithms: SIFT, SURF, and more recently BRISK to name a few. We have developped a keypoint descriptor inspired by the human visual system and more precisely the retina, coined Fast Retina Keypoint (FREAK).FREAKs are in general faster to compute with lower memory load and also more robust than SIFT, SURF or BRISK.
top

© alahi {at} stanford.edu
updated: January 2015

Follow me on

Alahi on ScholarAlahi on LinkedinAlahi on Twitter

 

Schools Studied


Stanford


Ecole Polytechnique Fédérale de Lausanne


Labs Worked

Vision lab at Stanford

LTS2

Transpor


Companies Worked

VisioSafe