nourani Goto Github PK
Name: Navid Nourani-Vatani
Type: User
Company: FleetSpark
Location: Germany
Blog: nourani.dk
Name: Navid Nourani-Vatani
Type: User
Company: FleetSpark
Location: Germany
Blog: nourani.dk
A set of Matlab functions to operate on a taxanomical hierarchy
Segment labeling front-end based on the Berkley BSR code
C++ implementation of the Local Binary Pattern texture descriptors. This class integrates with OpenCV and FFTW3 to bring a complete and fast implementation of the popular descriptors: LBP u2, ri, riu2 & hf. The routines for calculating these descriptors are inspired by the Matlab code of the original authors.
robot_localization is a package of nonlinear state estimation nodes. The package was developed by Charles River Analytics, Inc.
A C++11 template class to deal with units inside the program
This method takes a segmented (monochrome) image and assigns a numerical * label to each segment. * The method recursively called the OpenCV functions minMaxLoc and floodfill * to get the next unlabeled segment and fill it, respectively.
A demonstration of visual odometry for car-like vehicles using a downward looking camera. Please refer to the publications: [1] Navid Nourani-Vatani and Paulo VK Borges, Correlation-based Visual Odometry for Car-like Vehicles, Journal of Field Robotics, September 2011 [2] Navid Nourani-Vatani, Jonathan Roberts and Mandyam V Srinivasan, Practical Visual Odometry for Car-like Vehicles, IEEE International conference on Robotics and Automation, May 2009 [3] Navid Nourani-Vatani, Jonathan Roberts and Mandyam V Srinivasan, IMU-aided Visual Odometry for Car-like Vehicles, Australasian conference on Robotics and Automation, Dec 2008 I would love to hear from you if you are using this software and finding it useful or finding bugs (They say ~10 for every 1000 lines of code, so there are probably about 15-17 of these in there!) You can contact me at [email protected] Enjoy Navid
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