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 | % */
|
---|
39 | function [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 | |
---|
54 | NumMatches = size(X,2); |
---|
55 | Thre = 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; |
---|