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Ladybug Interface for MATLAB

This library is a Matlab/MEX-Wrapper for the Ladybug API provided by PointGrey. The code is provided AS IS without any warranty. See readme file for compiling instructions and the examples for usage instructions.

The code is provided free to use for research purposes. Please refer to the following paper when you are using it in your work:

T.Albrecht, T.Tan, G.West, T.Ly. Omnidirectional Video Stabilisation On a Virtual Camera Using Sensor Fusion. Proceedings of the 11th International Conference on Control, Autoation, Robotics and Vision, 2010.

Ladybug Coordinate Transforms for MATLAB

MATLAB implementations of coordinate transforms for virtual cameras and panoramas.

The code is provided free to use for research purposes. Please refer to the following paper when you are using it in your work:
T.Albrecht, T.Tan, G.West, T.Ly. Omnidirectional Video Stabilisation On a Virtual Camera Using Sensor Fusion. Proceedings of the 11th International Conference on Control, Autoation, Robotics and Vision, 2010.

Example: Convert points in a virtual camera into 3d camera coordinates:

% set virtual camera properties
  im_sz = [256,512];
  RCV = [sqrt(.5),-sqrt(.5),0;sqrt(.5),sqrt(.5),0;0,0,1];
  fov = 60;
						
% generate random points
  pV = ceil(rand(200,2).*repmat(im_sz,200,1));

% plot points in virtual camera
  figure; plot(pV(:,2),pV(:,1),'rx')

% convert into cartesian coordinates
  pV = sub2cart(pV,im_sz);

% convert into camera coordinates
  pC = CT_VCam2Camera(pV,RCV,fov,im_sz);

% plot result
  plot3(pC(:,1),pC(:,2),pC(:,3),'rx');
  figure; axis equal; axis([-1 1 -1 1 -1 1]);

Shipspotting Dataset for Visual Attention

A list images and ground truth data is available for download:

Please note that we only provide links to the image data and that all images are the property of their respective photographers.

The ground truth data is provided free to use for research purposes. Please refer to the following paper when you use the ground truth data in your work:

[3] T.Albrecht, G.West, T.Ly. Visual Maritime Attention Using Multiple Low-Level Features and Naïve Bayes Classification. Accepted for publication at the International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2011.