13.1.1.1 Aspect Graphs, Matching Systems, Object Recognition

Chapter Contents (Back)
Object Recognition. Matching, Volumes. Aspect Graphs. Matching, Aspect Graphs.

Basri, R.,
Viewer-Centered Representations in Object Recognition: A Computational Approach,
HPRCV97(Chapter V:4). (Massachusetts Inst. Tech) BibRef 9700

Seibert, M.C., and Waxman, A.M.,
Adaptive 3-D Object Recognition from Multiple Views,
PAMI(14), No. 2, February 1992, pp. 107-124.
IEEE DOI Given a sequence of views, accumulate the recognition and transformation parameters. At any time, the highest one is the winner, but it can change as new views are added. Uses unoccluded objects. BibRef 9202

Gigus, Z., Canny, J., and Seidel, R.,
Efficiently Computing and Representing Aspect Graphs of Polyhedral Objects,
PAMI(13), No. 6, June 1991, pp. 542-551.
IEEE DOI BibRef 9106
Earlier: ICCV88(30-39).
IEEE DOI Partition the viewing space and generate representative views of objects. BibRef

Laurentini, A.,
Comments on: Efficiently Computing and Representing Aspect Graphs of Polyhedral Objects,
PAMI(18), No. 1, January 1996, pp. 57-58.
IEEE DOI See
See also Efficiently Computing and Representing Aspect Graphs of Polyhedral Objects. BibRef 9601

Reeves, A.P., and Taylor, R.W.,
Identification of Three-Dimensional Objects Using Range Information,
PAMI(11), No. 4, April 1989, pp. 403-410.
IEEE DOI BibRef 8904
Earlier: with Prokop, R.J.,
Shape Analysis of Three Dimensional Objects Using Range Information,
CVPR85(452-457). Moments. Cornell Univ. Synthetic range data. Moment based feature vector classification. Models for all (icosahedron) view points are computed.
See also Three-Dimensional Shape Analysis Using Moments and Fourier Descriptors. BibRef

Kriegman, D.J.[David J.],
Computing Stable Poses of Piecewise Smooth Objects,
CVGIP(55), No. 2, March 1992, pp. 109-118.
Elsevier DOI BibRef 9203
Earlier: CADBV91(66-75). Restrict the pose because the object is on a plane. Solve polynomial equations for surfaces represented as algebraic equations. BibRef

Kriegman, D.J., and Ponce, J.,
Computing Exact Aspect Graphs of Curved Objects: Solids of Revolution,
IJCV(5), No. 2, November 1990, pp. 119-135.
Springer DOI BibRef 9011
And: 3DWS89(116-122). BibRef

Pae, S.I.[Sung-Il], Ponce, J.[Jean],
Toward a Scale-Space Aspect Graph: Solids of Revolution,
CVPR99(II: 196-201).
IEEE DOI BibRef 9900

Petitjean, S., Ponce, J., and Kriegman, D.J.,
Computing Exact Aspect Graphs of Curved Objects: Algebraic Surfaces,
IJCV(9), No. 3, 1992, pp. 231-255.
Springer DOI BibRef 9200
Earlier: A2, A1, A3: ECCV92(599-614).
Springer DOI BibRef
And: A1, A2, A3:
Computing Exact Aspect Graphs of Curved Objects: Parametric Patches,
AAAI-90(1074-1079). BibRef
And: UIUCDCS-R-90-1579, University of Illinois, 1990. BibRef

Petitjean, S.,
The Enumerative Geometry of Projective Algebraic-Surfaces and the Complexity of Aspect Graphs,
IJCV(19), No. 3, August 1996, pp. 261-287.
Springer DOI BibRef 9608
Earlier:
On the Enumerative Geometry of Aspect Graphs,
ECCV94(A:421-426).
Springer DOI Exact results for the degrees of visual event surfaces with piecewise-smooth algebraic objects. BibRef

Petitjean, S.[Sylvain],
Algebraic Geometry and Computer Vision: Polynomial Systems, Real and Complex Roots,
JMIV(10), No. 3, May 1999, pp. 191-220.
DOI Link BibRef 9905
Earlier:
Algebraic Geometry and Object Representation in Computer Vision,
ORCV94(155-165).
Springer DOI 9412
BibRef

Petitjean, S.[Sylvain],
Geometrie enumerative et contacts de varietes lineares: Application aux graphes d'aspects objets courbes,
Ph.D.Thesis, Institut National Polytechnique de Lorraine, 1995. BibRef 9500

Plantinga, H., and Dyer, C.R.,
The Asp: A Continuous Viewer-Centered Representation for 3D Object Recognition,
ICCV87(626-630). BibRef 8700

Plantinga, H., and Dyer, C.R.,
Visibility, Occlusion, and the Aspect Graph,
IJCV(5), No. 2, November 1990, pp. 137-160.
Springer DOI BibRef 9011
And: TR 736, CSD, Univ. of WisconsinDecember 1987. Contrast this with Ikeuchi's approach. BibRef

Korn, M.R.[Matthew R.], Dyer, C.R.[Charles R.],
3-D Multiview Object Representations for Model-Based Object Recognition,
PR(20), No. 1, 1987, pp. 91-103.
Elsevier DOI BibRef 8700

Rieger, J.H., Rohr, K.,
Semi-Algebraic Solids in 3-Space: A Survey of Modeling Schemes and Implications for View Graphs,
IVC(12), No. 7, September 1994, pp. 395-410.
Elsevier DOI Survey, 3D. BibRef 9409

Rieger, J.H.,
The Geometry of View Space of Opaque Objects Bounded by Smooth Surfaces,
AI(44), No. 1-2, July 1990, pp. 1-40.
Elsevier DOI This discusses how to compute the viewspace of objects. BibRef 9007

Rieger, J.H.,
Global Bifurcation Sets and Stable Projections of Nonsingular Algebraic Surfaces,
IJCV(7), No. 3, April 1992, pp. 171-194.
Springer DOI More on the generation of viewgraphs. BibRef 9204

Rieger, J.H.,
On the Complexity and Computation of View Graphs of Piecewise-Smooth Algebraic Surfaces,
TRFBI-HH-M-228/93, Universitat Hamburg, 1993. BibRef 9300

Wiskott, L.[Laurenz], von der Malsburg, C.[Christoph],
A Neural System for the Recognition of Partially Occluded Objects in Cluttered Scenes: A Pilot Study,
PRAI(7), 1993, pp. 935-948. BibRef 9300

Yuan, X.B.[Xiao-Bu], Lu, S.W.[Si-Wei],
Resolving View Sensitivity With Surface Locality,
PR(29), No. 9, September 1996, pp. 1485-1493.
Elsevier DOI Topological Structure. Geometric Uncertainty. Disambiguating Features. Range Images. BibRef 9609

Yuan, X.B.[Xiao-Bu], Lu, S.W.[Si-Wei],
Feature Mapping and View Planning with Localized Surface Parameters,
JMIV(7), No. 2, March 1997, pp. 163-174.
DOI Link 9705
BibRef

Malik, R.[Raashid], and Whangbo, T.[Taegkeun],
Angle Densities and Recognition of 3D Objects,
PAMI(19), No. 1, January 1997, pp. 52-57.
IEEE DOI 9702
BibRef
Earlier:
Using Angle Densities for 3-D Recognition,
SPIE(2354), October 1994, pp. 308-319. You cannot use uniform distributions of view in a view sphere. BibRef

Malik, R.[Raashid],
Polyhedral Object Recognition Using View Density,
SMC-C91(I:111-116). BibRef 9100

Whangbo, T.[Taegkeun],
3-D Object Recognition Using Angle View Densities,
Ph.D.Thesis, EECS, Stevens Institute, May 1995. BibRef 9505

Weinshall, D., Werman, M.,
On View Likelihood and Stability,
PAMI(19), No. 2, February 1997, pp. 97-108.
IEEE DOI 9703
How likely is a view to occur (i.e. a typical or characteristic view), and how little the image changes with small viewpoint changes are the same. Choose the most likely among all feasible solutions. BibRef

Weinshall, D., Werman, M., Tishby, N.,
Stability and Likelihood of Views of Three Dimensional Objects,
ECCV94(A:24-35).
Springer DOI BibRef 9400

Gdalyahu, Y.[Yoram], Weinshall, D.[Daphna], and Werman, M.[Michael],
Canonical Views, or the Stability and Likelihood of Images of 3D Objects,
ARPA94(II:967-971). BibRef 9400

Weinshall, D.[Daphna], and Werman, M.[Michael],
A Computational Theory of Canonical Views,
ARPA96(1001-1006). BibRef 9600

Weinshall, D.[Daphna], Werman, M.,
Disambiguation Techniques for Recognition in Large Databases and for Under-Constrained Reconstruction,
SCV95(425-430).
IEEE DOI The Hebrew University of Jerusalem. uses 4 kinds of matching, points, angles, cooluding countous, and shaded images of surfaces. BibRef 9500

Shimshoni, I.[Ilan], Ponce, J.[Jean],
Finite-Resolution Aspect Graphs Of Polyhedral Objects,
PAMI(19), No. 4, April 1997, pp. 315-327.
IEEE DOI 9705
BibRef
Earlier: WQV93(140-150). Computing the aspect graph of a polyhedral object using an orthographic camera with limited spatial resolution. This combines some different views under normal projection and results in accidental views in a finite area of space.
See also Probabilistic 3D Object Recognition. BibRef

Zhou, G.Q.,
Primitive Recognition Using Aspect-Interpretation Model-Matching in Both CAD-Based and LP-Based Measurement Systems,
PandRS(52), No. 2, April 1997, pp. 74-84. 9705
BibRef

To, F.W., Tsang, K.M.,
Recognition of Partially Occluded Objects Using an Orthogonal Complex AR Model Approach,
PRAI(13), No. 1, February 1999, pp. 85. BibRef 9902

Hinterstoisser, S.[Stefan], Cagniart, C.[Cedric], Ilic, S.[Slobodan], Sturm, P.F.[Peter F.], Navab, N.[Nassir], Fua, P.[Pascal], Lepetit, V.[Vincent],
Gradient Response Maps for Real-Time Detection of Textureless Objects,
PAMI(34), No. 5, May 2012, pp. 876-888.
IEEE DOI 1204
Real-time 3-D instance detection. Novel image representation for template matching. BibRef

Hinterstoisser, S.[Stefan], Lepetit, V.[Vincent], Ilic, S.[Slobodan], Fua, P.[Pascal], Navab, N.[Nassir],
Dominant orientation templates for real-time detection of texture-less objects,
CVPR10(2257-2264).
IEEE DOI 1006
BibRef

Hinterstoisser, S.[Stefan], Holzer, S.[Stefan], Cagniart, C.[Cedric], Ilic, S.[Slobodan], Konolige, K.G.[Kurt G.], Navab, N.[Nassir], Lepetit, V.[Vincent],
Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes,
ICCV11(858-865).
IEEE DOI 1201
Multi-modal (image and depth map), templates on different modalities. BibRef

Ulrich, M.[Markus], Wiedemann, C.[Christian], Steger, C.T.[Carsten T.],
Combining Scale-Space and Similarity-Based Aspect Graphs for Fast 3D Object Recognition,
PAMI(34), No. 10, October 2012, pp. 1902-1914.
IEEE DOI 1208
Recognize instance and determine pose. Hierarchical search for pose BibRef

Wang, M.[Meng], Gao, Y.[Yue], Lu, K.[Ke], Rui, Y.[Yong],
View-Based Discriminative Probabilistic Modeling for 3D Object Retrieval and Recognition,
IP(22), No. 4, April 2013, pp. 1395-1407.
IEEE DOI 1303
BibRef

Hu, W.Z.[Wen-Ze], Zhu, S.C.[Song-Chun],
Learning 3D Object Templates by Quantizing Geometry and Appearance Spaces,
PAMI(37), No. 6, June 2015, pp. 1190-1205.
IEEE DOI 1506
Dynamic programming BibRef

Hu, W.Z.[Wen-Ze], Zhu, S.C.[Song-Chun],
Learning a probabilistic model mixing 3D and 2D primitives for view invariant object recognition,
CVPR10(2273-2280).
IEEE DOI 1006
stick-like primitives. BibRef

Hu, W.Z.[Wen-Ze],
Learning 3D object templates by hierarchical quantization of geometry and appearance spaces,
CVPR12(2336-2343).
IEEE DOI 1208
BibRef

Busto, P.P.[Pau Panareda], Gall, J.[Juergen],
Open Set Domain Adaptation,
ICCV17(754-763)
IEEE DOI 1802
Award, Marr Prize, HM. image classification, learning (artificial intelligence), object recognition, closed set recognition task, Training BibRef

Busto, P.P.[Pau Panareda], Liebelt, J.[Joerg], Gall, J.[Juergen],
Adaptation of Synthetic Data for Coarse-to-Fine Viewpoint Refinement,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Kehl, W.[Wadim], Tombari, F.[Federico], Navab, N.[Nassir], Ilic, S.[Slobodan], Lepetit, V.[Vincent],
Hashmod: A Hashing Method for Scalable 3D Object Detection,
BMVC15(xx-yy).
DOI Link 1601
Object and pose in RGB-D. BibRef

Liu, A.A.[An-An], Nie, W.Z.[Wei-Zhi], Su, Y.T.[Yu-Ting],
3D Object Retrieval Based on Multi-View Latent Variable Model,
CirSysVideo(29), No. 3, March 2019, pp. 868-880.
IEEE DOI 1903
Solid modeling, Feature extraction, Computational modeling, Cameras, Visualization, Context modeling, Multi-View BibRef

Cong, Y.[Yang], Tian, D.Y.[Dong-Ying], Feng, Y.[Yun], Fan, B.J.[Bao-Jie], Yu, H.B.[Hai-Bin],
Speedup 3-D Texture-Less Object Recognition Against Self-Occlusion for Intelligent Manufacturing,
Cyber(49), No. 11, November 2019, pp. 3887-3897.
IEEE DOI 1908
feature extraction, iterative methods, object detection, object recognition, parallel processing, pose estimation, pose estimation BibRef

Su, Y.T.[Yu-Ting], Li, Y.Q.[Yu-Qian], Song, D.[Dan], Liu, A.[Anan], Nie, J.[Jie],
Joint Intermediate Domain Generation and Distribution Alignment for 2D Image-Based 3D Objects Retrieval,
MultMed(23), 2021, pp. 2127-2138.
IEEE DOI 2107
MDI3D Dataset. Visualization, Task analysis, Shape, Feature extraction, feature learning BibRef

Peng, Y.[Yang], Yan, S.[Shen], Liu, Y.X.[Yu-Xiang], Liu, Y.[Yu], Zhang, M.[Maojun],
View graph construction for scenes with duplicate structures via graph convolutional network,
IET-CV(16), No. 5, 2022, pp. 389-402.
DOI Link 2207
graph convolutional network, image embedding, metric learing, view graph construction BibRef


Hwang, S.[Sukjun], Heo, M.[Miran], Oh, S.W.[Seoung Wug], Kim, S.J.[Seon Joo],
Cannot See the Forest for the Trees: Aggregating Multiple Viewpoints to Better Classify Objects in Videos,
CVPR22(17031-17040)
IEEE DOI 2210
Vocabulary, Codes, Annotations, Detectors, Benchmark testing, Robustness, Scene analysis and understanding, Video analysis and understanding BibRef

Konishi, Y.[Yoshinori], Hanzawa, Y.[Yuki], Kawade, M.[Masato], Hashimoto, M.[Manabu],
Fast 6D Pose Estimation from a Monocular Image Using Hierarchical Pose Trees,
ECCV16(I: 398-413).
Springer DOI 1611
To structure search of templates BibRef

Son, J.H.[Jeong-Ho], Choi, S.H.[Sung-Hee],
Orientation selection for printing 3D models,
IC3D15(1-6)
IEEE DOI 1603
computational geometry BibRef

Zhang, X.Z.[Xiao-Zheng], Gao, Y.S.[Yong-Sheng], Caelli, T.[Terry],
Parametric Manifold of an Object under Different Viewing Directions,
ECCV12(V: 186-199).
Springer DOI 1210
BibRef

Mark, L.H., Okouneva, G., Saint-Cyr, P., Ignakov, D., English, C.,
Near-Optimal Selection of Views and Surface Regions for ICP Pose Estimation,
ISVC10(II: 53-63).
Springer DOI 1011
BibRef

Raytchev, B.[Bisser], Kikutsugi, Y.[Yuta], Tamaki, T.[Toru], Kaneda, K.[Kazufumi],
Class-Specific Low-Dimensional Representation of Local Features for Viewpoint Invariant Object Recognition,
ACCV10(III: 250-261).
Springer DOI 1011
BibRef

Raytchev, B.[Bisser], Mino, T.[Tetsuya], Tamaki, T.[Toru], Kaneda, K.[Kazufumi],
View-Invariant Object Recognition with Visibility Maps,
ICPR10(1040-1043).
IEEE DOI 1008
BibRef

Arie-Nachimson, M.[Mica], Basri, R.[Ronen],
Constructing implicit 3D shape models for pose estimation,
ICCV09(1341-1348).
IEEE DOI 0909
Rigid objects, pose in single 2D images. Voting procedure handle 3D transformations and self-occlusions. BibRef

Heisele, B.[Bernd], Kim, G.[Gunhee], Meyer, A.[Andrew],
Object Recognition with 3d Models,
BMVC09(xx-yy).
PDF File. 0909
From the 3-D graphical model. BibRef

Kosecka, J., Yang, X.L.[Xiao-Long],
Global localization and relative pose estimation based on scale-invariant features,
ICPR04(IV: 319-322).
IEEE DOI 0409
BibRef

Nölle, M.[Michael],
Distribution Distance Measures Applied to 3-D Object Recognition: A Case Study,
DAGM03(84-91).
Springer DOI 0310
dissimilarity measures for probability distributions. view-based object recognition. BibRef

Fitzgibbon, A.W., Fisher, R.B.,
Practical Aspect-Graph Derivation Incorporating Feature Segmentation Performance,
BMVC92(580-589).
PDF File. viewsphere, geometric modelling
PS File. BibRef 9200 Edinburgh BibRef

Fisher, R.B.,
Reducing Viewsphere Complexity,
ECAI90(274-276). aspect graphs BibRef 9000 Edinburgh BibRef

Verri, A., Uras, C.,
Aspect-Based Object Recognition with Size Functions,
ICPR96(I: 682-686).
IEEE DOI 9608
(Univ. di Genova, I) BibRef

Dunker, J., Hartmann, G., Stoehr, M.,
Single View Recognition and Pose Estimation of 3D Objects Using Sets of Prototypical Views and Spatially Tolerant Contour Representations,
ICPR96(IV: 14-18).
IEEE DOI 9608
(Univ. of Paderborn, D) BibRef

Herbin, S.[Stephane],
Recognizing 3D Objects by Generating Random Actions,
CVPR96(35-40).
IEEE DOI Active Vision. Simulated. BibRef 9600

Burns, J.B., and Riseman, E.M.,
Matching Complex Images to Multiple 3D Objects Using View Description Networks,
CVPR92(328-334).
IEEE DOI BibRef 9200
And: DARPA92(675-682). Almost an aspect graph type of match, but not quite. BibRef

Burns, J.B.[J. Brian],
Matching 2D Images to Multiple 3D Objects Using View Description Networks,
UMassTR-92-17, February 1992. BibRef 9202 Ph.D.Thesis, CS. BibRef

Burns, J.B.[J. Brian], and Kitchen, L.J.[Leslie J.],
Recognition in 2D Images of 3D Objects from Large Model Bases Using Prediction Hierarchies,
IJCAI87(763-766). BibRef 8700
And:
Rapid Object Recognition From a Large Model Base Using Prediction Hierarchies,
DARPA88(711-719). BibRef

Munkelt, O., Zierl, C.,
Fast 3-D Object Recognition Using Feature Based Aspect-Trees,
ICPR94(A:854-857).
IEEE DOI Find the best matching aspect using features computed from the 2D image. BibRef 9400

Lanser, S.[Stefan], Munkelt, O.[Olaf], Zierl, C.[Christoph],
Robust Video-Based Object Recognition Using CAD Models,
IAS95(529-536). BibRef 9500

Matsuo, H., Iwata, A.,
3-D Object Recognition Using MEGI Model from Range Data,
ICPR94(A:843-846).
IEEE DOI BibRef 9400

Matsuo, H., Funabashi, J., Iwata, A.,
3-D Object Recognition Using Adaptive Scale MEGI,
ICPR96(IV: 117-122).
IEEE DOI 9608
(Nagoya Institute of Technology, J) BibRef

Bellaire, G., Schlüns, K.[Karsten], Mitritz, A., Gwinner, K.,
Adaptive matching using object modes generated from photometric stereo images,
CIAP95(293-298).
Springer DOI 9509
Surface Normal Images BibRef

Schutte, K., Boersema, G.,
Hypothesizing a 3-D Scene from a Segmented Aerial Image,
O3DMT93(452-459). BibRef 9300

Tropf, H., and Walter, I.,
An ATN Model for 3D Recognition of Solids in Single Views,
IJCAI83(1094-1098). (Karlsruhe) Recognize Three-Dimensional Objects. (Aspect graphs - no.) Uses the ATN model to build a program for object recognition. BibRef 8300

Tropf, H.,
Analysis-by-Synthesis Search for Semantic Segmentation Applied to Workpiece Recognition,
ICPR80(241-244). BibRef 8000

Sripradisvarakul, T.[Thawach], and Jain, R.C.[Ramesh C.],
Generating Aspect Graphs for Curved Objects,
3DWS89(109-115). BibRef 8900

Watts, N.A.,
Calculating the Principal Views of a Polyhedron,
ICPR88(I: 316-322).
IEEE DOI BibRef 8800
And: Univ. of RochesterTR 234, 1987. BibRef

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Aspect Graph Matching -- Bowyer .


Last update:Nov 26, 2024 at 16:40:19