10.1.2 Stereo Analysis: Point Matching, Low Level Feature Matching

Chapter Contents (Back)
Matching, Points. Matching, Stereo. Stereo, Point Matching.

Cottafava, G., and LeMoli, G.,
The Automated Contour Map,
CACM(12), No. 7, July 1969, pp. 386-391. BibRef 6907

Mori, K., Kidode, M., and Asada, H.,
An Iterative Prediction and Correction Method for Automatic Stereo Comparison,
CGIP(2), 1973, pp. 393-401. BibRef 7300

Dev, P.,
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Grimson, W.E.L.,
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PAMI(7), No. 1, January 1985, pp. 17-34. BibRef 8501
And: MIT AI Memo-762, January 1984. Stereo, Grimson. Description of the new Grimson algorithm that uses the modifications suggested by the work since 1980. The major changes are in the area of matching. Very detailed description of the algorithm and the implementation. See also From Images to Surfaces: A Computational Study of the Human Early Visual System. BibRef

Drumheller, M., and Poggio, T.A.,
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CRA87(527-538). BibRef 8700
And: Same title. CRA86(1439-1448). BibRef

Drumheller, M.,
Connection Machine Stereomatching,
AAAI-86(748-753). BibRef 8600

White, S.,
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DARPA92(391-399). Scale space extraction of disparities. BibRef 9200

Prazdny, K.,
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Jones, D.G., Malik, J.,
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IVC(10), No. 10, December 1992, pp. 699-708.
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Earlier: ECCV92(395-410).
Springer DOI BibRef
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Gerstenberger, J.S.[Jeffrey S.],
Mechanism for determining parallax between digital images,
US_Patent5,220,441, Jun 15, 1993
WWW Link. Correlation matching. BibRef 9306

Kara, A.[Atsushi], Wilkes, D.M.[D. Mitchell], Kawamura, K.[Kazuhiko],
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CVGIP(60), No. 3, November 1994, pp. 392-397.
WWW Link. BibRef 9411

Reimann, D., Haken, H.,
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BioCyber(71), No. 1, 1994, pp. 17-26. Disparity at each point, relaxation process. BibRef 9400

Agouris, P., Schenk, T.,
Automated Aerotriangulation Using Multiple Image Multipoint Matching,
PhEngRS(62), No. 6, June 1996, pp. 703-710. 9606
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Toth, C.K., Krupnik, A.,
Concept, Implementation, and Results of an Automatic Aerotriangulation System,
PhEngRS(62), No. 6, June 1996, pp. 711-717. 9606
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Toth, C.K.[Charles K.], Schenk, T.[Toni],
Multiple image matching in an automatic aerotriangulation system,
CAIP93(750-758).
Springer DOI 9309
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March, R.,
Computation of Stereo Disparity Using Regularization,
PRL(8), 1988, pp. 181-187. BibRef 8800

March, R.,
A Regularization Model for Stereo Vision with Controlled Continuity,
PRL(10), 1989, pp. 259-263. BibRef 8900

Baillard, C., Dissard, O., Jamet, O., Maitre, H.,
Extraction and Textural Characterization of Aboveground Areas from Aerial Stereo Pairs: A Quality Assessment,
PandRS(53), No. 2, April 1998, pp. 130-141. 9805
See also Above-Ground Objects in Urban Scenes from Medium Scale Aerial Imagery. BibRef

Scharstein, D.[Daniel], Szeliski, R.S.[Richard S.],
Stereo Matching With Nonlinear Diffusion,
IJCV(28), No. 2, June-July 1998, pp. 155-174.
DOI Link 9808
BibRef
Earlier: CVPR96(343-350).
IEEE DOI BibRef
And: CornellComputer Science, TR96-1575, March 1996. Code, Stereo. Code:
HTML Version. Point matching using Sum of Squared Differences (SSD). BibRef

Sinha, S.N.[Sudipta Narayan], Scharstein, D.[Daniel], Szeliski, R.[Richard],
Efficient High-Resolution Stereo Matching Using Local Plane Sweeps,
CVPR14(1582-1589)
IEEE DOI 1409
plane sweep;semi-global matching;stereo matching BibRef

Scharstein, D.,
Matching Images by Comparing Their Gradient Fields,
ICPR94(A:572-575).
IEEE DOI BibRef 9400

Szeliski, R.S.[Richard S.], Scharstein, D.,
Symmetric Sub-Pixel Stereo Matching,
ECCV02(II: 525 ff.).
Springer DOI 0205
BibRef

Chen, T.Y., Bovik, A.C.[Alan C.], Cormack, L.K.[Lawrence K.],
Stereoscopic Ranging by Matching Image Modulations,
IP(8), No. 6, June 1999, pp. 785-797.
IEEE DOI BibRef 9906

Liu, Y., Cormack, L.K.[Lawrence K.], Bovik, A.C.[Alan C.],
Statistical Modeling of 3-D Natural Scenes With Application to Bayesian Stereopsis,
IP(20), No. 9, September 2011, pp. 2515-2530.
IEEE DOI 1109
BibRef

Su, C.C.[Che-Chun], Cormack, L.K.[Lawrence K.], Bovik, A.C.[Alan C.],
Color and Depth Priors in Natural Images,
IP(22), No. 6, 2013, pp. 2259-2274.
IEEE DOI stereo image processing; image discontinuity; Gabor filter bank 1307
BibRef
Earlier: A1, A3, A2:
Statistical model of color and disparity with application to Bayesian stereopsis,
Southwest12(169-172).
IEEE DOI 1205
BibRef
Earlier: A1, A3, A2:
Natural scene statistics of color and range,
ICIP11(257-260).
IEEE DOI 1201
BibRef

Su, C.C.[Che-Chun], Cormack, L.K.[Lawrence K.], Bovik, A.C.[Alan C.],
Closed-Form Correlation Model of Oriented Bandpass Natural Images,
SPLetters(22), No. 1, January 2015, pp. 21-25.
IEEE DOI 1410
image processing BibRef

Su, C.C.[Che-Chun], Cormack, L.K.[Lawrence K.], Bovik, A.C.[Alan C.],
Oriented Correlation Models of Distorted Natural Images With Application to Natural Stereopair Quality Evaluation,
IP(24), No. 5, May 2015, pp. 1685-1699.
IEEE DOI 1504
Computational modeling BibRef

Birchfield, S.T.[Stan T.], Tomasi, C.[Carlo],
Depth Discontinuities by Pixel-to-Pixel Stereo,
IJCV(35), No. 3, December 1999, pp. 269-293.
DOI Link BibRef 9912
Earlier: ICCV98(1073-1080).
IEEE DOI BibRef
And: STAN-CS--TR-96-1573, Stanford Univ. July 1996. BibRef

Mühlmann, K.[Karsten], Maier, D.[Dennis], Hesser, J.[Jürgen], Männer, R.[Reinhard],
Calculating Dense Disparity Maps from Color Stereo Images, an Efficient Implementation,
IJCV(47), No. 1-3, April-June 2002, pp. 79-88.
DOI Link 0203
BibRef
Earlier: SMBV01(xx-yy). 0110
BibRef

Wiora, G.[Georg], Babrou, P.[Pavel], Männer, R.[Reinhard],
Real Time High Speed Measurement of Photogrammetric Targets,
DAGM04(562-569).
Springer DOI 0505
BibRef

Okutomi, M.[Masatoshi], Katayama, Y.[Yasuhiro], Oka, S.[Setsuko],
A Simple Stereo Algorithm to Recover Precise Object Boundaries and Smooth Surfaces,
IJCV(47), No. 1-3, April-June 2002, pp. 261-273.
DOI Link 0203
BibRef
Earlier: CVPR01(II:138-144).
IEEE DOI 0110
BibRef
And: A1, A2 only:
Simple Stereo Algorithm to Recover Precise Object Boundaries and Smooth Surfaces,
SMBV01(xx-yy). 0110
Area based matching. Adaptive. Use multiple pairs and multiple windows to limit area matching errors. BibRef

Lhuillier, M.[Maxime], Quan, L.[Long],
Match Propagation for Image-Based Modeling and Rendering,
PAMI(24), No. 8, August 2002, pp. 1140-1146.
IEEE Abstract. 0208
Image Based Rendering. Start from sparse set of seed matches, propagate to neighbors. The procedure can generate inbetween images (blended images). BibRef

Lhuillier, M.[Maxime], Quan, L.[Long],
A Quasi-Dense Approach to Surface Reconstruction from Uncalibrated Images,
PAMI(27), No. 3, March 2005, pp. 418-433.
IEEE Abstract. 0501
BibRef
Earlier:
Quasi-Dense Reconstruction from Image Sequence,
ECCV02(II: 125 ff.).
Springer DOI 0205
BibRef
Earlier:
Robust Dense Matching Using Local and Global Geometric Constraints,
ICPR00(Vol I: 968-972).
IEEE DOI 0009
Structure from resampled dense matches rather than just feature points. BibRef

Zeng, G.[Gang], Paris, S.[Sylvain], Quan, L.[Long], Lhuillier, M.[Maxime],
Surface Reconstruction by Propagating 3D Stereo Data in Multiple 2D Images,
ECCV04(Vol I: 163-174).
Springer DOI 0405
See also Accurate and Scalable Surface Representation and Reconstruction from Images. BibRef

Lhuillier, M.,
Efficient Dense Matching for Textured Scenes using Region Growing,
BMVC98(xx-yy). BibRef 9800

Xiao, J.X.[Jian-Xiong], Chen, J.N.[Jing-Ni], Yeung, D.Y.[Dit-Yan], Quan, L.[Long],
Learning Two-View Stereo Matching,
ECCV08(III: 15-27).
Springer DOI 0810
BibRef

Binaghi, E.[Elisabetta], Gallo, I.[Ignazio], Marino, G.[Giuseppe], Raspanti, M.[Mario],
Neural adaptive stereo matching,
PRL(25), No. 15, November 2004, pp. 1743-1758.
WWW Link. 0411
BibRef

Binaghi, E.[Elisabetta], Gallo, I.[Ignazio], Guidali, A., Raspanti, M.[Mario], Salvini, G.,
Adaptive Neural Regularization Assignment for Semi-Blind Biomedical Image Restoration,
IMVIP07(207-207).
IEEE DOI 0709
BibRef

Gallo, I.[Ignazio], Binaghi, E.[Elisabetta], Raspanti, M.[Mario],
Neural disparity computation for dense two-frame stereo correspondence,
PRL(29), No. 5, 1 April 2008, pp. 673-687.
WWW Link. 0802
Stereo matching; Occlusion; Disparity space; Neural networks BibRef

Vanetti, M.[Marco], Gallo, I.[Ignazio], Binaghi, E.[Elisabetta],
Dense Two-Frame Stereo Correspondence by Self-organizing Neural Network,
CIAP09(1035-1042).
Springer DOI 0909
BibRef

Gallo, I.[Ignazio], Binaghi, E.[Elisabetta],
Dense Stereo Matching with Growing Aggregation and Neural Learning,
VISAPP06(343-353).
Springer DOI 0711
BibRef

Sarkar, I., Bansal, M.,
A Wavelet-Based Multiresolution Approach to Solve the Stereo Correspondence Problem Using Mutual Information,
SMC-B(37), No. 4, August 2007, pp. 1009-1014.
IEEE DOI 0707
BibRef

Sizintsev, M.[Mikhail], Wildes, R.P.[Richard P.],
Coarse-to-fine stereo vision with accurate 3D boundaries,
IVC(28), No. 3, March 2010, pp. 352-366.
Elsevier DOI 1001
BibRef
Earlier:
Efficient Stereo with Accurate 3-D Boundaries,
BMVC06(I:237).
PDF File. 0609
Computer vision; Stereo; Coarse-to-fine; Occlusions; Real-time algorithms See also Spatiotemporal Stereo and Scene Flow via Stequel Matching. BibRef

Sizintsev, M.[Mikhail],
Hierarchical Stereo with Thin Structures and Transparency,
CRV08(97-104).
IEEE DOI 0805
BibRef

Shi, C.B.[Chen-Bo], Wang, G.J.[Gui-Jin], Pei, X.K.[Xiao-Kang], He, B.[Bei], Lin, X.G.[Xing-Gang],
Stereo Matching Using Local Plane Fitting in Confidence-Based Support Window,
IEICE(E95-D), No. 2, February 2012, pp. 699-702.
WWW Link. 1202
BibRef

Shi, C.B.[Chen-Bo], Wang, G.J.[Gui-Jin], Pei, X.K.[Xiao-Kang], He, B.[Bei], Lin, X.G.[Xing-Gang],
An Interleaving Updating Framework of Disparity and Confidence Map for Stereo Matching,
IEICE(E95-D), No. 5, May 2012, pp. 1552-1555.
WWW Link. 1202
See also High-Accuracy Stereo Matching Based on Adaptive Ground Control Points. BibRef

Stentoumis, C., Grammatikopoulos, L., Kalisperakis, I., Karras, G.E.,
On accurate dense stereo-matching using a local adaptive multi-cost approach,
PandRS(91), No. 1, 2014, pp. 29-49.
Elsevier DOI 1404
BibRef
Earlier:
Implementing An Adaptive Approach For Dense Stereo-matching,
ISPRS12(XXXIX-B5:309-314).
DOI Link 1209
BibRef

Stentoumis, C., Grammatikopoulos, L., Kalisperakis, I., Petsa, E., Karras, G.E.,
A Local Adaptive Approach for Dense Stereo Matching in Architectural Scene Reconstruction,
3DARCH13(219-226).
DOI Link 1308
BibRef

Kalisperakis, I.[Ilias], Karras, G.E.[George E.], Grammatikopoulos, L.[Lazaros],
3D Aspects of 2D Epipolar Geometry,
PCV06(xx-yy).
PDF File. 0609
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Joglekar, J., Gedam, S.S., Mohan, B.K.,
Image Matching Using SIFT Features and Relaxation Labeling Technique: A Constraint Initializing Method for Dense Stereo Matching,
GeoRS(52), No. 9, September 2014, pp. 5643-5652.
IEEE DOI 1407
Bayes methods BibRef


Berjón, D.[Daniel], Pagés, R.[Rafael], Morán, F.[Francisco],
Fast feature matching for detailed point cloud generation,
IPTA16(1-6)
IEEE DOI 1703
computer graphics BibRef

Mizukami, Y.[Yoshiki], Okada, K.[Koichi], Nomura, A.[Atsushi], Nakanishi, S.[Shinya], Tadamura, K.[Katsumi],
Sub-pixel disparity search for binocular stereo vision,
ICPR12(364-367).
WWW Link. 1302
BibRef

Li, Y.J.[Yu-Jun], Au, O.C.[Oscar C.], Xu, L.F.[Ling-Feng], Sun, W.X.[Wen-Xiu], Chui, S.H.[Sung-Him], Kwok, C.W.[Chun-Wing],
A convex-optimization approach to dense stereo matching,
ICIP11(1005-1008).
IEEE DOI 1201
BibRef

Zhang, H.F.[Hao-Feng], Zhao, C.X.[Chun-Xia], Tang, Z.M.[Zhen-Min], Yang, J.Y.[Jing-Yu],
Particle swarm based stereo algorithm and disparity map evaluation,
ICARCV08(1511-1514).
IEEE DOI 1109
BibRef

Einecke, N.[Nils], Eggert, J.[Julian],
Evaluation of Direct Plane Fitting for Depth and Parameter Estimation,
DICTA10(492-497).
IEEE DOI 1012
BibRef
And:
A Two-Stage Correlation Method for Stereoscopic Depth Estimation,
DICTA10(227-234).
IEEE DOI 1012
BibRef

Lang, H.T.[Hai-Tao], Wang, Y.T.[Yong-Tian], Qi, X.[Xin], Pan, W.Q.[Wei-Qing],
Enhanced point descriptors for dense stereo matching,
IASP10(228-231).
IEEE DOI 1004
BibRef

Zhao, G.Q.[Gang-Qiang], Chen, L.[Ling], Chen, G.C.[Gen-Cai],
A Speeded-Up Local Descriptor for dense stereo matching,
ICIP09(2101-2104).
IEEE DOI 0911
BibRef

Miyazawa, K.[Kazuyuki], Aoki, T.[Takafumi],
A robot-based 3D body scanning system using passive stereo vision,
ICIP08(305-308).
IEEE DOI 0810
BibRef

Shibahara, T.[Takuma], Aoki, T.[Takafumi], Nakajima, H.[Hiroshi], Kobayashi, K.[Koji],
A Sub-Pixel Stereo Correspondence Technique Based on 1D Phase-only Correlation,
ICIP07(V: 221-224).
IEEE DOI 0709
BibRef

Galarza, L., Candocia, F.M.,
Optimal and Dense Small Baseline Stereo Image Correspondence,
ICIP06(1037-1040).
IEEE DOI 0610
BibRef

Zhou, W.[Wei], Kambhamettu, C.[Chandra],
Binocular Stereo Dense Matching in the Presence of Specular Reflections,
CVPR06(II: 2363-2370).
IEEE DOI 0606
BibRef

Schlesinger, D.[Dmitrij], Flach, B.[Boris], Shekhovtsov, A.[Alexander],
A Higher Order MRF-Model for Stereo-Reconstruction,
DAGM04(440-446).
Springer DOI 0505
BibRef

Bovyrin, A., Eruhimov, V., Molinov, S., Mosyagin, V., Pisarevsky, V.,
Fast and robust dense stereo correspondence by column segmentation,
ICIP03(III: 1033-1036).
IEEE DOI 0312
BibRef

Jin, K., Boufama, B.,
Towards a Fast and Reliable Dense Matching Algorithm,
VI02(178).
PDF File. 0208
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Falkenhagen, L.[Lutz], Wedi, T.[Thomas],
Improving Block-Based Disparity Estimation by Considering the Non-uniform Distribution of the Estimation Error,
SMILE98(xx-yy). BibRef 9800

El Zaart, A., Ziou, D.[Djemel], Dubeau, F.[Francois],
Phase-Based Disparity Estimation: a Spatial Approach,
ICIP97(III: 244-247).
IEEE DOI BibRef 9700

Maimone, M.W.[Mark W.], and Shafer, S.A.[Steven A.],
Modeling Foreshortening in Stereo Vision using Local Spatial Frequency,
IROS95(xx). BibRef 9500
And: CMU-CS-TR-95-104, January 1995. Gabor Filter. Phase-Based.
HTML Version. (Html based) and
PS File. (postscript). Plus Errata:
PS File. BibRef

Maimone, M.W.[Mark W.],
Characterizing Stereo Matching Problems using Local Spatial Frequency,
CMU-CS-TR-96-125, May 1996. BibRef 9605 Ph.D.Thesis.
PS File. BibRef

Hannah, M.J.,
Computer Matching of Areas in Stereo Imagery,
Ph.D.Thesis (CS), 1978. BibRef 7800 Stanford AIMemo 239 BibRef
And: Stanford CS Memo STAN-CS-74-438, July 1978. Precursor of Gennery and follower of Quam. Stereo analysis with arbitrary initial camera locations. Computes the camera model by least squares error analysis from a set of matching points. Extends the area of matching points by growing regions which have the same or close disparities. BibRef

Hannah, M.J.,
Bootstrap Stereo,
AAAI-80(38-40). BibRef 8000
And: DARPA80(201-208). BibRef
And:
Bootstrap Stereo Error Simulations,
DARPA81(131-135). A sequence of images is used to generate motion and depth information. The first pair is used to provide an estimate of the camera changes and to give some 3-D information to be used in the sequence. The new areas of the images are analyzed to find new feature points for the next image in the sequence. BibRef

Hannah, M.J.,
SRI's Baseline Stereo System,
DARPA85(149-155). Find matches at different scales using lower levels to guide the higher resolution matches. BibRef 8500

Hannah, M.J.,
Test Results from SRI's Stereo System,
DARPA88(740-744). Results on the photogrammetry data set for the stereo program. BibRef 8800

Hannah, M.J.,
Detection of Errors in Match Disparities,
DARPA82(283-285). BibRef 8200

Gennery, D.B.,
Modelling the Environment of an Exploring Vehicle by Means of Stereo Vision,
Ph.D.June 1980. BibRef 8006 Stanford BibRef

Gennery, D.B.,
Object Detection and Measurement Using Stereo Vision,
DARPA80(161-167). BibRef 8000
And: IJCAI79(320-327). BibRef
Earlier:
A Stereo Vision System for an Autonomous Vehicle,
IJCAI77(576-582). BibRef
And:
A Stereo Vision System,
DARPAO77(31-46). See also Visual Tracking of Known Three-Dimensional Objects. BibRef

Arnold, R.D., and Binford, T.O.,
Geometric Constraints in Stereo Vision,
SPIE(238), San Diego, CA, July 1980, pp. 281-292. BibRef 8007

Arnold, R.D.,
Automated Stereo Perception,
Ph.D.Thesis (cs), 1983. BibRef 8300 Stanford AIMemo 351 BibRef
And: Stanford CS Memo STAN-CS-83-961. BibRef
Earlier:
Local Context in Matching Edges for Stereo Vision,
DARPA78(65-72). BibRef
Earlier:
Spatial Understanding,
DARPA77(1-4). Combines the work of Moravec and Gennery to do a match using corner type features. BibRef

Szeliski, R.S.[Richard S.], and Hinton, G.E.[Geoffrey E.],
Solving Random-Dot Stereograms Using the Heat Equation,
CVPR85(284-288). Simplification of the new work of Prazdny, by implementing as Heat equation. BibRef 8500

Essafi, H., Mazzoni, C., Julien, P.,
Satellite Digital Elevation Model on the Heterogeneous OPENVISION Parallel Computer,
CAMP95(xx). BibRef 9500

Koschan, A.F., Rodehorst, V., Spiller, K.,
Color Stereo Vision Using Hierarchical Block Matching and Active Color Illumination,
ICPR96(I: 835-839).
IEEE DOI 9608
(Technical Univ. of Berlin, D) BibRef

Koschan, A.F., Rodehorst, V.,
Towards Real-Time Stereo Employing Parallel Algorithms for Edge-Based and Dense Stereo Matching,
CAMP95(xx). BibRef 9500

Koschan, A.F.[Andreas F.],
Dense stereo correspondence using polychromatic block matching,
CAIP93(538-542).
Springer DOI 9309
BibRef

Shah, J.,
A Nonlinear Diffusion Model for Discontinuous Disparity and Half-Occlusions in Stereo,
CVPR93(34-40).
IEEE DOI An approach to stereo correspondence. BibRef 9300

Xie, M.[Ming], Thonnat, M.[Monique],
A theory of 3D reconstruction of heterogeneous edge primitives from two perspective views,
ECCV92(715-719).
Springer DOI 9205
BibRef

Bandopadhy, A.,
Interest Points, Disparities and Correspondence,
DARPA84(184-187). (U. of Rochester) BibRef 8400

Shizawa, M.,
Direct Estimation of Multiple Disparities for Transparent Multiple Surfaces in Binocular Stereo,
ICCV93(447-454).
IEEE DOI Developed from work in motion section on transparent surfaces. See also On visual ambiguities due to transparency in motion and stereo. BibRef 9300

Gennert, M.A.,
Brightness-Based Stereo Matching,
ICCV88(139-143).
IEEE DOI BibRef 8800

Sato, T.,
Automotive Stereo Vision Using Deconvolution Technique,
IJCAI79(763-765). BibRef 7900

Chapter on Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular continues in
Edge Based Stereo Analysis: Scan Line Oriented .


Last update:Jun 24, 2017 at 21:08:28