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 [FeaVector] = genFeaVector(f,fsup,VList,HList,i,near,NeighborFeaList);
|
---|
40 | %function [FeaVector] = genFeaVector(f,fsup,RowTop,RowBottom,ColumnLeft,ColumnRight,i,NeighborFeaList);
|
---|
41 | % This function set the feature to the right format of Feature Vector
|
---|
42 | global GeneralDataFolder ScratchDataFolder LocalFolder ClusterExecutionDirectory...
|
---|
43 | ImgFolder VertYNuPatch VertYNuDepth HoriXNuPatch HoriXNuDepth a_default b_default Ox_default Oy_default...
|
---|
44 | Horizon_default filename NuRow_default;
|
---|
45 |
|
---|
46 | if nargin < 7
|
---|
47 | NeighborFeaList = 1:5;
|
---|
48 | end
|
---|
49 |
|
---|
50 | NuRow = NuRow_default;
|
---|
51 |
|
---|
52 | % load pics info
|
---|
53 | PicsinfoName = strrep(filename{i},'img','picsinfo');
|
---|
54 | temp = dir([GeneralDataFolder '/PicsInfo/' PicsinfoName '.mat']);
|
---|
55 | if size(temp,1) == 0
|
---|
56 | a = a_default;
|
---|
57 | b = b_default;
|
---|
58 | Ox = Ox_default;
|
---|
59 | Oy = Oy_default;
|
---|
60 | Horizon = Horizon_default;
|
---|
61 | else
|
---|
62 | load([GeneralDataFolder '/PicsInfo/' PicsinfoName '.mat']);
|
---|
63 | end
|
---|
64 |
|
---|
65 | % generate the range of the row for the same thi (weight value)
|
---|
66 | %RowskyBottom = floor(NuRow/2);
|
---|
67 | %PatchSkyBottom = ceil(VertYNuDepth*(1-Horizon));
|
---|
68 | %if row <= RowskyBottom
|
---|
69 | % PatchRowRatio = PatchSkyBottom/RowskyBottom;
|
---|
70 | % RowTop = round((row-1)*PatchRowRatio+1);
|
---|
71 | % RowBottom = round(row*PatchRowRatio);
|
---|
72 | %else
|
---|
73 | % PatchRowRatio = (VertYNuDepth-PatchSkyBottom)/(NuRow-RowskyBottom);
|
---|
74 | % RowTop = round((row-RowskyBottom-1)*PatchRowRatio+1)+PatchSkyBottom;
|
---|
75 | % RowBottom = round((row-RowskyBottom)*PatchRowRatio)+PatchSkyBottom;
|
---|
76 | %end
|
---|
77 |
|
---|
78 | FeaVector = [];
|
---|
79 | % Superpixel Feature
|
---|
80 | if size(fsup,2)~=0
|
---|
81 | shift = [0 0; -1 0; 1 0; 0 -1; 0 1]; % left right top bottom
|
---|
82 | for l = 1:1
|
---|
83 | [Ix Iy] = meshgrid(max(min(HList+shift(l,1),HoriXNuDepth),1),...
|
---|
84 | max(min(VList+shift(l,2),VertYNuDepth),1));
|
---|
85 | maskNeibor = sub2ind([VertYNuDepth, HoriXNuDepth], Iy(:), Ix(:));
|
---|
86 | if (sum(sum(Iy==1))== size(Iy(:),1) && l ==4) || (sum(sum( Iy == VertYNuDepth ))== size(Iy(:),1) && l ==5)
|
---|
87 | FeaVector =[ FeaVector ;(conv2(fsup(:,f(maskNeibor,1)),[0.25; 0.25; 0.25; 0.25],'same'))];
|
---|
88 | else
|
---|
89 | FeaVector =[ FeaVector ;fsup(:,f(maskNeibor,1))];
|
---|
90 | end
|
---|
91 | end
|
---|
92 | end
|
---|
93 | % Hi Resolution
|
---|
94 | shift = [0 0; -1 0; 1 0; 0 -1; 0 1];
|
---|
95 |
|
---|
96 | for l = NeighborFeaList
|
---|
97 | [Ix Iy] = meshgrid(max(min(HList+shift(l,1),HoriXNuDepth),1),...
|
---|
98 | max(min(VList+shift(l,2),VertYNuDepth),1));
|
---|
99 | maskNeibor = sub2ind([VertYNuDepth, HoriXNuDepth], Iy(:), Ix(:));
|
---|
100 | if (sum(sum(Iy==1))== size(Iy(:),1) && l ==4)||(sum(sum( Iy == VertYNuDepth ))== size(Iy(:),1) && l ==5)
|
---|
101 | FeaVector =[ FeaVector ;(conv2(f(maskNeibor,2:35),[0.25; 0.25; 0.25; 0.25],'same'))'];
|
---|
102 | else
|
---|
103 | FeaVector =[ FeaVector ;f(maskNeibor,2:35)'];
|
---|
104 | end
|
---|
105 | end
|
---|
106 |
|
---|
107 | % Med 1/3 Resolution
|
---|
108 | if near ~=1
|
---|
109 | shift = 3*[0 0; -1 0; 1 0; 0 -1; 0 1];
|
---|
110 | end
|
---|
111 | for l = NeighborFeaList
|
---|
112 | [Ix Iy] = meshgrid(max(min(HList+shift(l,1),HoriXNuDepth),1),...
|
---|
113 | max(min(VList+shift(l,2),VertYNuDepth),1));
|
---|
114 | maskNeibor = sub2ind([VertYNuDepth, HoriXNuDepth], Iy(:), Ix(:));
|
---|
115 | if (sum(sum(Iy==1))== size(Iy(:),1) && l ==4)||(sum(sum( Iy == VertYNuDepth ))== size(Iy(:),1) && l ==5)
|
---|
116 | FeaVector =[ FeaVector ;(conv2(f(maskNeibor,36:69),[0.25; 0.25; 0.25; 0.25],'same'))'];
|
---|
117 | else
|
---|
118 | FeaVector =[ FeaVector ;f(maskNeibor,36:69)'];
|
---|
119 | end
|
---|
120 | end
|
---|
121 |
|
---|
122 | % Low 1/9 REsolution
|
---|
123 | if near ~=1
|
---|
124 | shift = 9*[0 0; -1 0; 1 0; 0 -1; 0 1];
|
---|
125 | end
|
---|
126 | for l = NeighborFeaList
|
---|
127 | [Ix Iy] = meshgrid(max(min(HList+shift(l,1),HoriXNuDepth),1),...
|
---|
128 | max(min(VList+shift(l,2),VertYNuDepth),1));
|
---|
129 | maskNeibor = sub2ind([VertYNuDepth, HoriXNuDepth], Iy(:), Ix(:));
|
---|
130 | if (sum(sum(Iy==1))== size(Iy(:),1) && l ==4)||(sum(sum( Iy == VertYNuDepth ))== size(Iy(:),1) && l ==5)
|
---|
131 | FeaVector =[ FeaVector ;(conv2(f(maskNeibor,70:103),[0.25; 0.25; 0.25; 0.25],'same'))'];
|
---|
132 | else
|
---|
133 | FeaVector =[ FeaVector ;f(maskNeibor,70:103)'];
|
---|
134 | end
|
---|
135 | end
|
---|
136 |
|
---|
137 | % other features
|
---|
138 | shift = [0 0];%; -1 0; 1 0; 0 -1; 0 1];
|
---|
139 | for l = 1:1
|
---|
140 | [Ix Iy] = meshgrid(max(min(HList+shift(l,1),HoriXNuDepth),1),...
|
---|
141 | max(min(VList+shift(l,2),VertYNuDepth),1));
|
---|
142 | maskNeibor = sub2ind([VertYNuDepth, HoriXNuDepth], Iy(:), Ix(:));
|
---|
143 | %if (sum(sum(Iy==1))== size(Iy(:),1) && l ==4)||(sum(sum( Iy == VertYNuDepth ))== size(Iy(:),1) && l ==5)
|
---|
144 | % maskNeibor2 = sub2ind([VertYNuDepth, HoriXNuDepth], Iy(:)+1, Ix(:));
|
---|
145 | % FeaVector =[ FeaVector ;(f(maskNeibor,104)+f(maskNeibor2,104))'/2];
|
---|
146 | %else
|
---|
147 | FeaVector =[ FeaVector ;f(maskNeibor,104)'];
|
---|
148 | %end
|
---|
149 | end
|
---|
150 |
|
---|