[37] | 1 | % * This code was used in the following articles:
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| 2 | % * [1] Learning 3-D Scene Structure from a Single Still Image,
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| 3 | % * Ashutosh Saxena, Min Sun, Andrew Y. Ng,
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| 4 | % * In ICCV workshop on 3D Representation for Recognition (3dRR-07), 2007.
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| 5 | % * (best paper)
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| 6 | % * [2] 3-D Reconstruction from Sparse Views using Monocular Vision,
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| 7 | % * Ashutosh Saxena, Min Sun, Andrew Y. Ng,
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| 8 | % * In ICCV workshop on Virtual Representations and Modeling
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| 9 | % * of Large-scale environments (VRML), 2007.
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| 10 | % * [3] 3-D Depth Reconstruction from a Single Still Image,
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| 11 | % * Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng.
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| 12 | % * International Journal of Computer Vision (IJCV), Aug 2007.
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| 13 | % * [6] Learning Depth from Single Monocular Images,
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| 14 | % * Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng.
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| 15 | % * In Neural Information Processing Systems (NIPS) 18, 2005.
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| 16 | % *
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| 17 | % * These articles are available at:
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| 18 | % * http://make3d.stanford.edu/publications
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| 19 | % *
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| 20 | % * We request that you cite the papers [1], [3] and [6] in any of
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| 21 | % * your reports that uses this code.
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| 22 | % * Further, if you use the code in image3dstiching/ (multiple image version),
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| 23 | % * then please cite [2].
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| 24 | % *
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| 25 | % * If you use the code in third_party/, then PLEASE CITE and follow the
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| 26 | % * LICENSE OF THE CORRESPONDING THIRD PARTY CODE.
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| 27 | % *
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| 28 | % * Finally, this code is for non-commercial use only. For further
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| 29 | % * information and to obtain a copy of the license, see
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| 30 | % *
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| 31 | % * http://make3d.stanford.edu/publications/code
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| 32 | % *
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| 33 | % * Also, the software distributed under the License is distributed on an
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| 34 | % * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
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| 35 | % * express or implied. See the License for the specific language governing
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| 36 | % * permissions and limitations under the License.
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| 37 | % *
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| 38 | % */
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| 39 | function [GroundLevel] = CalGroundLevel(defaultPara, ImgInfo, Pair) |
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| 40 | |
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| 41 | % This function generate the ground level at the first pair of process |
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| 42 | |
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| 43 | % =========estimating ground level using ground in imgA and imgB on image A coordinate |
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| 44 | |
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| 45 | % GroundLevel is in Global_Scale=================== |
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| 46 | ImgInfo(1).Model.Depth.FitDepth = ImgInfo(1).Model.Depth.FitDepth*Pair.DepthScale(1); |
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| 47 | ImgInfo(2).Model.Depth.FitDepth = ImgInfo(2).Model.Depth.FitDepth*Pair.DepthScale(2); |
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| 48 | % ================================================= |
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| 49 | % cleaning Groundmask for A |
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| 50 | RangePercent = 100; |
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| 51 | [Dy Dx] = size( ImgInfo(1).Model.Depth.FitDepth); |
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| 52 | APositionAll = im_cr2w_cr(ImgInfo(1).Model.Depth.FitDepth, permute(ImgInfo(1).Model.Ray,[2 3 1])); |
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| 53 | AY_median = median( APositionAll(2,ImgInfo(1).Model.maskG)); |
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| 54 | ADistant2Ay_median = (APositionAll(2,ImgInfo(1).Model.maskG) - AY_median); |
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| 55 | ANumber_YMedian = round( sum(APositionAll(2,ImgInfo(1).Model.maskG)<AY_median)*RangePercent/100); |
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| 56 | [Avalue AIndexSort] = sort(ADistant2Ay_median); |
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| 57 | AYmedia_mark = AIndexSort(1:ANumber_YMedian); |
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| 58 | AGround_mark = zeros(Dy, Dx); |
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| 59 | temp = zeros(sum(ImgInfo(1).Model.maskG(:)) ,1); |
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| 60 | temp(AYmedia_mark) = 1; |
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| 61 | AGround_mark(ImgInfo(1).Model.maskG) = temp; |
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| 62 | AGround_mark = logical(AGround_mark); |
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| 63 | % finishing cleaning Groundmask for A |
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| 64 | |
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| 65 | % cleaning Groundmask for B |
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| 66 | BPositionAll = im_cr2w_cr(ImgInfo(2).Model.Depth.FitDepth, permute(ImgInfo(2).Model.Ray,[2 3 1])); |
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| 67 | BWrlPosition = Pair.R'*BPositionAll(:,:)+repmat( -Pair.R'*Pair.T, 1, size(BPositionAll(:,:),2)); |
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| 68 | BWrlPosition = reshape(BWrlPosition,3,55,[]); |
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| 69 | BY_median = median( BWrlPosition(2,ImgInfo(2).Model.maskG)); |
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| 70 | BDistant2By_median = (BWrlPosition(2,ImgInfo(2).Model.maskG) - BY_median); |
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| 71 | BNumber_YMedian = round( sum(BWrlPosition(2,ImgInfo(2).Model.maskG)<BY_median)*RangePercent/100); |
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| 72 | [Bvalue BIndexSort] = sort(BDistant2By_median); |
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| 73 | BYmedia_mark = BIndexSort(1:BNumber_YMedian); |
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| 74 | BGround_mark = zeros(Dy, Dx); |
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| 75 | temp = zeros(sum(ImgInfo(2).Model.maskG(:)) ,1); |
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| 76 | temp(BYmedia_mark) = 1; |
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| 77 | BGround_mark(ImgInfo(2).Model.maskG) = temp; |
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| 78 | BGround_mark = logical( BGround_mark); |
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| 79 | % finishing cleaning Groundmask for B |
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| 80 | |
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| 81 | % find the jointly median of the ground of image AB in Y direction |
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| 82 | GroundLevel = median([ APositionAll(2,AGround_mark) BWrlPosition(2,BGround_mark)]); % Now Ground is in Img1 Img2 pair scale |
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| 83 | GroundLevel = GroundLevel/Pair.DepthScale(1); % rescale to the Img1 local scale |
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| 84 | |
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| 85 | return; |
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