source: proiecte/pmake3d/make3d_original/Make3dSingleImageStanford_version0.1/image3dstiching/ransac/EstDepMatchDist.m @ 37

Last change on this file since 37 was 37, checked in by (none), 14 years ago

Added original make3d

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1% *  This code was used in the following articles:
2% *  [1] Learning 3-D Scene Structure from a Single Still Image,
3% *      Ashutosh Saxena, Min Sun, Andrew Y. Ng,
4% *      In ICCV workshop on 3D Representation for Recognition (3dRR-07), 2007.
5% *      (best paper)
6% *  [2] 3-D Reconstruction from Sparse Views using Monocular Vision,
7% *      Ashutosh Saxena, Min Sun, Andrew Y. Ng,
8% *      In ICCV workshop on Virtual Representations and Modeling
9% *      of Large-scale environments (VRML), 2007.
10% *  [3] 3-D Depth Reconstruction from a Single Still Image,
11% *      Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng.
12% *      International Journal of Computer Vision (IJCV), Aug 2007.
13% *  [6] Learning Depth from Single Monocular Images,
14% *      Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng.
15% *      In Neural Information Processing Systems (NIPS) 18, 2005.
16% *
17% *  These articles are available at:
18% *  http://make3d.stanford.edu/publications
19% *
20% *  We request that you cite the papers [1], [3] and [6] in any of
21% *  your reports that uses this code.
22% *  Further, if you use the code in image3dstiching/ (multiple image version),
23% *  then please cite [2].
24% * 
25% *  If you use the code in third_party/, then PLEASE CITE and follow the
26% *  LICENSE OF THE CORRESPONDING THIRD PARTY CODE.
27% *
28% *  Finally, this code is for non-commercial use only.  For further
29% *  information and to obtain a copy of the license, see
30% *
31% *  http://make3d.stanford.edu/publications/code
32% *
33% *  Also, the software distributed under the License is distributed on an
34% * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
35% *  express or implied.   See the License for the specific language governing
36% *  permissions and limitations under the License.
37% *
38% */
39function [dist, inlierThreDist] = EstReProjError(X, R, T, D1, D2, lamda1, lamda2, disp)
40
41% This function calculate the Estimated Reprojction Error for Match pairs
42% According to heuristic
43% Bigger Estimated Reprojction Error is lower the match is correct
44% Input
45%       X - calibrated corrdinate (normalize by depth)
46%       R - rotation matirx
47%       T - translation matrix (unit length)
48%   D1/2 - depth information
49%   lamda1/2 - triangulated depths
50% Return
51%       dist - distribution define according to the heuristic
52%       inlierThreDist - when EstDepMatchDist <= threDist it is a inlier
53
54NumMatches = size(X,2);
55Thre = Inf;
56%  X1 = X(1:3,:);
57%  X2 = X(4:6,:);
58%  X2_2 = X2.*repmat(D2, 3, 1);
59%  X1_2 = R*X1.*repmat(D1, 3, 1);
60
61 ops = sdpsettings('solver','sedumi','verbose',1);
62 a = sdpvar(1,1);
63 b = sdpvar(1,1);
64 F = set(a>=0)+set(b>=0);
65%  sol = solvesdp(F,norm(a*X1_2(:) + repmat(T, NumMatches, 1)-
66%  a*X2_2(:),2),ops);
67 sol = solvesdp(F,norm( lamda1*a - D1, 1)+norm( lamda2*b - D2, 1),ops);
68 a = double(a);
69 b = double(b);
70 EstReProjError = abs(D1./lamda2/a-lamda1./lamda2)+abs(D2./lamda1/b-lamda2./lamda1);
71 inlierThreDist = find(EstReProjError <= Thre);
72 if disp
73    figure(6);
74    hist(EstReProjError(inlierThreDist),1000);
75 end
76 
77 % fit exp distibution
78 parmhat = expfit(EstReProjError(inlierThreDist));
79 dist = exppdf(EstReProjError(inlierThreDist),parmhat);
80 return;
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