source: proiecte/pmake3d/make3d_original/Make3dSingleImageStanford_version0.1/image3dstiching/Refinement/CleanMatch.m @ 37

% *  This code was used in the following articles:
% *  [1] Learning 3-D Scene Structure from a Single Still Image, 
% *      Ashutosh Saxena, Min Sun, Andrew Y. Ng, 
% *      In ICCV workshop on 3D Representation for Recognition (3dRR-07), 2007.
% *      (best paper)
% *  [2] 3-D Reconstruction from Sparse Views using Monocular Vision, 
% *      Ashutosh Saxena, Min Sun, Andrew Y. Ng, 
% *      In ICCV workshop on Virtual Representations and Modeling 
% *      of Large-scale environments (VRML), 2007. 
% *  [3] 3-D Depth Reconstruction from a Single Still Image, 
% *      Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng. 
% *      International Journal of Computer Vision (IJCV), Aug 2007. 
% *  [6] Learning Depth from Single Monocular Images, 
% *      Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng. 
% *      In Neural Information Processing Systems (NIPS) 18, 2005.
% *
% *  These articles are available at:
% *  http://make3d.stanford.edu/publications
% * 
% *  We request that you cite the papers [1], [3] and [6] in any of
% *  your reports that uses this code. 
% *  Further, if you use the code in image3dstiching/ (multiple image version),
% *  then please cite [2].
% *  
% *  If you use the code in third_party/, then PLEASE CITE and follow the
% *  LICENSE OF THE CORRESPONDING THIRD PARTY CODE.
% *
% *  Finally, this code is for non-commercial use only.  For further 
% *  information and to obtain a copy of the license, see 
% *
% *  http://make3d.stanford.edu/publications/code
% *
% *  Also, the software distributed under the License is distributed on an 
% * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either 
% *  express or implied.   See the License for the specific language governing 
% *  permissions and limitations under the License.
% *
% */
function [I] = CleanMatch(MatchesRaw, CoeffMRaw)
%function [Matches CoeffM I] = CleanMatch(MatchesRaw, CoeffMRaw)
% [Matches CoeffM] = CleanMatch(MatchesRaw, CoeffMRaw)
% Clear the MatchesRaw ensure there are only one to one matches
MatchDistThre = 10^2;
NumTarget = size(MatchesRaw,2);
MatchedPointsDist = permute( sum( ( repmat( MatchesRaw(3:4,:), [1 1 NumTarget]) - repmat( permute( MatchesRaw(3:4,:), [1 3 2]), [1 NumTarget 1]) ).^2, 1), [3 2 1]);
MaskMatchesTooCloseInd = find( MatchedPointsDist < MatchDistThre);
[MaskMatchesTooCloseRowInd dump]= find( MatchedPointsDist < MatchDistThre);
MatrixOFCoeff = zeros(NumTarget);
MatrixOFCoeff(MaskMatchesTooCloseInd) = CoeffMRaw( MaskMatchesTooCloseRowInd);
[ V I] =max(MatrixOFCoeff, [], 1);
I = unique(I);
% Matches = MatchesRaw(:,I);
% CoeffM = CoeffMRaw(I);

return;