11.9.2 Oct-Trees -- Use

Chapter Contents (Back)
Octree.

Hardas, D.M., and Srihari, S.N.,
Progressive Refinement of 3-D Images Using Coded Binary Trees: Algorithms and Architecture,
PAMI(6), No. 6, November 1984, pp. 748-757. BibRef 8411

Yau, M.M.[Mann-May],
Generating Quadtrees of Cross Sections from Octrees,
CVGIP(27), No. 2, August 1984, pp. 211-238.
Elsevier DOI Quadtrees of sections orthogonal to coordinate axis. BibRef 8408

Goldwasser, S.M., Reynolds, R.A.,
Real-Time Display And Manipulation Of 3-D Medical Objects: The Voxel Processor Architecture,
CVGIP( 39), No. 1, July 1987, pp. 1-27.
Elsevier DOI BibRef 8707

Chien, C.H., and Aggarwal, J.K.,
Model Construction and Shape Recognition from Occluding Contours,
PAMI(11), No. 4, April 1989, pp. 372-389.
IEEE DOI BibRef 8904
Earlier:
Reconstruction and Recognition of 3-D Objects from Occluding Contours and Silhouettes,
Univ. of Texas-TR-87-5-37. BibRef
Earlier:
Shape Recognition from Single Silhouettes,
ICCV87(481-490). Recognize Two-Dimensional Objects. This is a recognition of the 3-D object from feature points on the 2-D silhouette. First a hypothesis is generated for the match, then it is confirmed by using constraints imposed by the view point implied by the proposed match. 2D representation is by quadtrees and 3-D by Octrees. BibRef

Chien, C.H., and Aggarwal, J.K.,
Identification of 3D Objects from Multiple Silhouettes Using Quadtrees/Octrees,
CVGIP(36), No. 2/3, November/December 1986, pp. 256-273.
Elsevier DOI 3 non-coplanar views. BibRef 8611

Chien, C.H., and Aggarwal, J.K.,
Volume/Surface Octrees for the Representation of Three-Dimensional Objects,
CVGIP(36), No. 1, October 1986, pp. 100-113.
Elsevier DOI BibRef 8610
Earlier:
Computation of Volume/Surface Octrees from Contours and Silhouettes of Multiple Views,
CVPR86(250-255). BibRef
Earlier:
A Volume/Surface Octree Representation,
ICPR84(817-820). BibRef
Earlier:
Reconstruction and Matching of 3-D Objects using Quadtrees/Octrees,
CVWS85(49-54). Volumetric representation. Quadtree of different views is mapped into an octree. These are combined to get the full description. For quadtrees: See also Normalized Quadtree Representation, A. BibRef

Chien, C.H., Sim, Y.B., and Aggarwal, J.K.,
Generation of Volume/Surface Octree from Range Data,
CVPR88(254-260).
IEEE DOI Combining several views in the octree representation (from range data). BibRef 8800

Kim, Y.C., and Aggarwal, J.K.,
Rectangular Parallelepiped Coding: A Volumetric Representation of Three-Dimensional Objects,
RA(2), No. 3, Sept 1986, pp. 127-134. See also Positioning Three-Dimensional Objects Using Stereo Images. BibRef 8609

Kim, Y.C., and Aggarwal, J.K.,
Rectangular Parallelepiped Coding for Solid Modeling,
RA(1), No. 3, 1986, pp. 77-85. An extended version of the oct-tree concept. BibRef 8600

Kim, Y.C., and Aggarwal, J.K.,
Rectangular Coding for Binary Images,
CVPR83(108-113). BibRef 8300

Raviv, D., Pao, Y.H., and Loparo, K.A.,
Reconstruction of Three-Dimensional Surfaces from Two-Dimensional Binary Images,
RA(5), No. 5, October 1989, pp. 701-710. (May be in the wrong place.) BibRef 8905

Noborio, H., Fukuda, S., and Arimoto, S.,
Construction of the Octree Approximating Three-Dimensional Objects by Using Multiple Views,
PAMI(10), No. 6, November 1988, pp. 769-782.
IEEE DOI BibRef 8811
Earlier:
A Fast Algorithm for Building the Octree for a Three-Dimensional Object from Its Multiple Images,
ICPR88(II: 860-862).
IEEE DOI Uses a polyhedral cone generated from views of the object. Basic. BibRef

Brunet, P., Navazo, I.,
Solid Representation and Operation Using Extended Octrees,
TOG(9), 1990, pp. 170-197. BibRef 9000

Srivastava, S.K.[Sanjay K.], Ahuja, N.[Narendra],
Octree Generation from Object Silhouettes in Perspective Views,
CVGIP(49), No. 1, January 1990, pp. 68-84.
Elsevier DOI BibRef 9001

Ahuja, N.[Narendra], Veenstra, J.,
Generating Octrees from Object Silhouettes in Orthographic Views,
PAMI(11), No. 2, February 1989, pp. 137-149.
IEEE DOI BibRef 8902
Earlier: A2, A1:
Efficient Octree Generation from Silhouettes,
CVPR86(537-542). Viewing is from 13 standard views (3 faces, 6 edges, 4 corners), these provide a direct mapping from the view to the octree. Find the intersection of the octree space with the given image. BibRef

Veenstra, J., Ahuja, N.[Narendra],
Line Drawings of Octree-Represented Objects,
TOG(7), 1988, pp. 61-75. BibRef 8800

Ahuja, N.[Narendra], Nash, C.[Charles],
Octree Representations of Moving Objects,
CVGIP(26), No. 2, May 1984, pp. 207-216.
Elsevier DOI BibRef 8405
Earlier: A2, A1: CVPR83(380-381). Update while object under linear translation BibRef

Oase, W.M., Ahuja, N.,
Efficient Octree Representation of Moving Objects,
ICPR84(821-823). BibRef 8400

Weng, J.Y.[Ju-Yang], and Ahuja, N.[Narendra],
Octree Representation of Objects in Arbitrary Motion: Representation and Efficiency,
CVGIP(39), No. 2, August 1987, pp. 167-185.
Elsevier DOI BibRef 8708
Earlier: CVPR85(524-529). Representation problem, incremental changes in the octree. BibRef

Potmesil, M.[Michael],
Generating Octree Models of 3D Objects from Their Silhouettes in a Sequence of Images,
CVGIP(40), No. 1, October 1987, pp. 1-29.
Elsevier DOI BibRef 8710
Earlier:
Generating Models of Solid Objects by Matching 3D Surface Segments,
IJCAI83(1089-1093). BibRef
And:
Generating Three-Dimensional Surface Models of Solid Objects from Multiple Projections,
Ph.D.Thesis, 1982, BibRef RPI-IPL-TR-033. (Spatial matching of segments of an object to generate the complete 3D representation.) The series of 3-D conic volumes determined by the silhouette are intersected using octrees for the representation method. See also Generation of 3D Surface Descriptions from Images of Pattern Illuminated Objects. BibRef

Pujari, L.A.K.[Lavakusha Arun K.], Reddy, P.G.,
Linear Octrees by Volume Intersection,
CVGIP(45), No. 3, March 1989, pp. 371-379.
Elsevier DOI Intersection of 3 orthogonal silhouettes. BibRef 8903

Ibaroudene, D.[Djaffer], Demjanenko, V.[Victor], Acharya, R.S.[Raj S.],
Adjacency Algorithms for Linear Octree Nodes,
IVC(8), No. 2, May 1990, pp. 115-123.
Elsevier DOI rectangular (X,Y,Z) coordinate from octal locational code of linear octtree. BibRef 9005

Minovic, P., Ishikawa, S., and Kato, K.,
Symmetry Identification of a 3-D Object Represented by Octree,
PAMI(15), No. 5, May 1993, pp. 507-514.
IEEE DOI BibRef 9305

Szeliski, R.S.[Richard S.],
Rapid Octree Construction from Image Sequences,
CVGIP(58), No. 1, July 1993, pp. 23-32.
DOI Link BibRef 9307
Earlier:
Real-Time Octree Generation from Rotating Objects,
DEC-CRL-90-12, December 1990.
HTML Version. BibRef

Szeliski, R.S.,
Shape From Rotation,
CVPR91(625-631).
IEEE DOI BibRef 9100
And: DEC-CRL-90-13, December 1990.
HTML Version. Given OF and a rotating object determine shape. This is related to the slider stereo work. BibRef

Shu, R.B.[Ren Ben], Kankanhalli, M.S.[Mohan S.],
Efficient Linear Octree Generation from Voxels,
IVC(12), No. 5, June 1994, pp. 297-303.
Elsevier DOI First extract the surface, then partition into parallelpipeds. BibRef 9406

Bauer, M.A., Feeney, S.T., Gargantini, I.,
Parallel 3-D Filling with Octrees,
PDC(22), No. 1, 1994, pp. 121-128. Fill using the boundary. BibRef 9400

Whang, K.Y., Song, J.W., Chang, J.W., Kim, J.Y., Cho, W.S., Park, C.M., Song, I.Y.,
Octree-R: An Adaptive Octree for Efficient Ray-Tracing,
VCG(1), No. 4, December 1995, pp. 343-349. BibRef 9512

Nitya, V.B., Sridevi, N., Pujari, A.K.,
Linear Octree by Volume Intersection Using Perspective Silhouettes,
PRL(13), 1992, pp. 781-788. BibRef 9200

Pai, A.G., Usha, H., Pujari, A.K.,
Linear Octree of a 3D Object from 2D Silhouettes Using Segment Tree,
PRL(11), 1990, pp. 619-623. BibRef 9000

Vörös, J.,
A strategy for repetitive neighbor finding in octree representations,
IVC(18), No. 14, November 2000, pp. 1085-1091.
Elsevier DOI 0101
BibRef

Cointepas, Y.[Yann], Bloch, I.[Isabelle], Garnero, L.[Line],
A cellular model for multi-objects multi-dimensional homotopic deformations,
PR(34), No. 9, September 2001, pp. 1785-1798.
Elsevier DOI 0108
BibRef
Earlier:
Joined segmentation of cortical surface and brain volume in MRI using a homotopic deformable cellular model,
3DIM99(240-248).
IEEE DOI 9910
BibRef

Lim, S.H.[Suk-Hyun], Shin, B.S.[Byeong-Seok],
A distance template for octree traversal in CPU-based volume ray casting,
VC(24), No. 4, April 2008, pp. xx-yy.
Springer DOI 0804
BibRef

Bai, Y.[Ying], Han, X.[Xiao], Prince, J.L.[Jerry L.],
Digital Topology on Adaptive Octree Grids,
JMIV(34), No. 2, June 2009, pp. xx-yy.
Springer DOI 0906
BibRef
Earlier: CVPR07(1-8).
IEEE DOI 0706
BibRef
Earlier:
Octree-Based Topology-Preserving Isosurface Simplification,
MMBIA06(81).
IEEE DOI 0609
See also Moving Grid Framework for Geometric Deformable Models, A. BibRef

Lenz, R.[Reiner], Carmona, P.L.[Pedro Latorre],
Octahedral Transforms for 3-D Image Processing,
IP(18), No. 12, December 2009, pp. 2618-2628.
IEEE DOI 0912
Linear filters and generalizations of Fourier Transform. BibRef

Chen, W.C.[Wen-Chao], Chou, H.L.[Hong-Long], Chen, Z.[Zen],
A quality controllable multi-view object reconstruction method for 3D imaging systems,
JVCIR(21), No. 5-6, July-August 2010, pp. 427-441.
Elsevier DOI 1007
BibRef
Earlier: A3, A2, A1:
A performance controllable octree construction method,
ICPR08(1-4).
IEEE DOI 0812
3D imaging system; Modeling from silhouettes; Octree model; XOR projection error; System performance; Dynamic modeling; Progressive transmission; Multi-camera system BibRef

Leblanc, L.[Luc], Houle, J.[Jocelyn], Poulin, P.[Pierre],
Modeling with blocks,
VC(27), No. 6-8, June 2011, pp. 555-563.
WWW Link. 1107
BibRef

Goradia, R.[Rhushabh], Kashyap, M.S.S.[M. S. Sriram], Chaudhuri, P.[Parag], Chandran, S.[Sharat],
Tracing specular light paths in point-based scenes,
VC(27), No. 12, December 2011, pp. 1083-1097.
WWW Link. 1112
BibRef
Earlier: A2, A1, A3, A4:
Implicit surface octrees for ray tracing point models,
ICCVGIP10(227-234).
DOI Link 1111
BibRef

Elseberg, J.[Jan], Borrmann, D.[Dorit], Nüchter, A.[Andreas],
One billion points in the cloud: An octree for efficient processing of 3D laser scans,
PandRS(76), No. 1, February 2013, pp. 76-88.
Elsevier DOI 1301
Octree; Tree data structure; Data compression; Frustum culling; Ray casting; RANSAC; Nearest neighbor search BibRef

Su, Y.T.[Yun-Ting], Bethel, J.[James], Hu, S.W.[Shuo-Wen],
Octree-based segmentation for terrestrial LiDAR point cloud data in industrial applications,
PandRS(113), No. 1, 2016, pp. 59-74.
Elsevier DOI 1602
Terrestrial LiDAR BibRef

Zhang, Y.[Yi],
The D-FCM partitioned D-BSP tree for massive point cloud data access and rendering,
PandRS(120), No. 1, 2016, pp. 25-36.
Elsevier DOI 1610
Directional FCM BibRef

de Queiroz, R.L., Garcia, D.C., Chou, P.A., Florencio, D.A.,
Distance-Based Probability Model for Octree Coding,
SPLetters(25), No. 6, June 2018, pp. 739-742.
IEEE DOI 1806
encoding, geometry, octrees, probability, arithmetic coder, bit rate, context-driven method, distance-based probability model, point-cloud compression BibRef

Garcia, D.C., de Queiroz, R.L.,
Intra-Frame Context-Based Octree Coding for Point-Cloud Geometry,
ICIP18(1807-1811)
IEEE DOI 1809
BibRef
Earlier:
Context-based octree coding for point-cloud video,
ICIP17(1412-1416)
IEEE DOI 1803
Octrees, Encoding, Three-dimensional displays, Geometry, Decoding, Transform coding, real-time point-cloud transmission. Entropy, Image coding, Streaming media, 3D immersive video. real-time point-cloud transmission BibRef


Braeger, S.[Sarah], Foroosh, H.[Hassan],
Curvature Augmented Deep Learning for 3D Object Recognition,
ICIP18(3648-3652)
IEEE DOI 1809
Incorporate shape in CNN. Face, Shape, Training, Object recognition, Solid modeling, Computational modeling, Deep Learning BibRef

Riegler, G.[Gernot], Ulusoy, A.O.[Ali Osman], Geiger, A.[Andreas],
OctNet: Learning Deep 3D Representations at High Resolutions,
CVPR17(6620-6629)
IEEE DOI 1711
Arrays, Image resolution, Memory management, Octrees, Shape BibRef

Bhattacharya, S.[Sounak], Fan, L.X.[Li-Xin], Babahajiani, P.[Pouria], Gabbouj, M.[Moncef],
Global Scale Integral Volumes,
CVRoads16(I: 192-204).
Springer DOI 1611
Octtree for Lidar data. BibRef

Caraffa, L.[Laurent], Brédif, M.[Mathieu], Vallet, B.[Bruno],
3D Watertight Mesh Generation with Uncertainties from Ubiquitous Data,
ACCV16(IV: 377-391).
Springer DOI 1704
BibRef
Earlier:
3D Octree Based Watertight Mesh Generation from Ubiquitous Data,
GeoBigData15(613-617).
DOI Link 1602
BibRef

Nguyen, H.P.[Hoang-Phong], Hong, S.[Seungpyo], Kim, J.[Jinwook],
Hierarchical OBB-sphere tree for large-scale range data management,
ICIP13(839-843)
IEEE DOI 1402
Cameras BibRef

Sandberg, D., Forssen, P., Ogniewski, J.,
Model-Based Video Coding Using Colour and Depth Cameras,
DICTA11(158-163).
IEEE DOI 1205
E.g. Kinect. Model-based coding with camera motion and 3-D for key-frames. Quad-tree at key frame, linear camera motion between. BibRef

Mak, W.H.[Wai-Ho], Chan, M.Y.[Ming-Yuen], Wu, Y.C.[Ying-Cai], Chung, K.K.[Ka-Kei], Qu, H.M.[Hua-Min],
VoxelBars: An Informative Interface for Volume Visualization,
ISVC08(I: 161-170).
Springer DOI 0812
BibRef

Wu, Y.C.[Ying-Cai], Qu, H.M.[Hua-Min], Zhou, H.[Hong], Chan, M.Y.[Ming-Yuen],
Fusing Features in Direct Volume Rendered Images,
ISVC06(I: 273-282).
Springer DOI 0611
BibRef
And:
Focus + Context Visualization with Animation,
PSIVT06(1293-1302).
Springer DOI 0612
To visualize medical data. BibRef

Wong, H.C.[Hon-Cheng], Qu, H.M.[Hua-Min], Wong, U.H.[Un-Hong], Tang, Z.[Zesheng], Mueller, K.[Klaus],
A Perceptual Framework for Comparisons of Direct Volume Rendered Images,
PSIVT06(1314-1323).
Springer DOI 0612
BibRef

Lin, J.C.[Jun-Cong], Jin, X.G.[Xiao-Gang], Fan, Z.G.[Zhen-Gwen], Wang, C.C.L.[Charlie C. L.],
Automatic PolyCube-Maps,
GMP08(xx-yy).
Springer DOI 0804
BibRef

Lee, P.F.[Pai-Feng], Chiang, C.H.[Chien-Hsing], Tseng, J.L.[Juin-Ling], Jong, B.S.[Bin-Shyan], Lin, T.W.[Tsong-Wuu],
Octree Subdivision Using Coplanar Criterion for Hierarchical Point Simplification,
PSIVT06(54-63).
Springer DOI 0612
BibRef

Samet, H., Kochut, A.,
Octree approximation and compression methods,
3DPVT02(460-469). 0206
BibRef

Cano, P., Torres, J.C.,
Representation of Polyhedral Objects Using SP-Octrees,
WSCG02(95).
HTML Version. 0209
BibRef

Velasco, F., Torres, J.C.,
Cells Octree: A New Data Structure for Volume Modeling and Visualization,
VMV01(xx-yy).
PDF File. 0209
BibRef

Cheung, G.K.M.[German K. M.], Kanade, T.[Takeo], Bouguet, J.Y.[Jean-Yves], Holler, M.[Mark],
A Real Time System for Robust 3D Voxel Reconstruction of Human Motions,
CVPR00(II: 714-720).
IEEE DOI
PDF File.
HTML Version. 0005
BibRef

Sojan Lal, P., Unnikrishnan, A., Poulose Jacob, K.,
Parallel implementation of octtree generation algorithm,
ICIP98(III: 1005-1009).
IEEE DOI 9810
BibRef

Kitamura, Y., Kishino, F.,
A Parallel Algorithm for Octree Generation from Polyhedral Shape Representation,
ICPR96(IV: 303-309).
IEEE DOI 9608
(ATR Communication Systems, J) BibRef

Mori, T., Suzuki, S., Horikoshi, T., and Yasuno, T.,
Multi-Scale Structure from Multi-Views by d{2}G Filtered 3D Voting,
CVPR93(662-663).
IEEE DOI BibRef 9300

Connolly, C.I.,
Cumulative Generation of Octree Models from Range Data,
Conf. on RoboticsAtlanta, March 1984, pp. 25-32. BibRef 8403

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Occupancy Grids, Voxels .


Last update:Nov 17, 2018 at 09:12:27