11.2.4.1 Range and Color, RGB-D Segmentation and Analysis

Chapter Contents (Back)
Range Segmentation. RGB-D Segmentation. See also Color Applied to Segmentation.

Hulik, R.[Rostislav], Spanel, M.[Michal], Smrz, P.[Pavel], Materna, Z.[Zdenek],
Continuous plane detection in point-cloud data based on 3D Hough Transform,
JVCIR(25), No. 1, 2014, pp. 86-97.
Elsevier DOI 1502
Hough Transform. RGB-D sensor BibRef

Stückler, J.[Jörg], Behnke, S.[Sven],
Multi-resolution surfel maps for efficient dense 3D modeling and tracking,
JVCIR(25), No. 1, 2014, pp. 137-147.
Elsevier DOI 1502
BibRef
And: Corrigendum: JVCIR(26), No. 1, 2015, pp. 349-.
Elsevier DOI 1502
3D multi-resolution RGB-D image representation BibRef

Riaz, Z.[Zahid], Linder, T.[Thorsten], Behnke, S.[Sven], Worst, R.[Rainer], Surmann, H.[Hartmut],
Efficient Transmission and Rendering of RGB-D Views,
ISVC13(I:517-526).
Springer DOI 1310
BibRef

Liu, H.[Haowei], Philipose, M.[Matthai], Sun, M.T.[Ming-Ting],
Automatic objects segmentation with RGB-D cameras,
JVCIR(25), No. 4, 2014, pp. 709-718.
Elsevier DOI 1403
BibRef
Earlier:
Automatic object segmentation with 3-D cameras,
ICIP12(569-572).
IEEE DOI 1302
Boundary detection See also Recognizing object manipulation activities using depth and visual cues. BibRef

Richtsfeld, A.[Andreas], Mörwald, T.[Thomas], Prankl, J.[Johann], Zillich, M.[Michael], Vincze, M.[Markus],
Learning of perceptual grouping for object segmentation on RGB-D data,
JVCIR(25), No. 1, 2014, pp. 64-73.
Elsevier DOI 1502
Computer vision BibRef

Zhou, K.[Kai], Richtsfeld, A.[Andreas], Varadarajan, K.M.[Karthik Mahesh], Zillich, M.[Michael], Vincze, M.[Markus],
Combining Plane Estimation with Shape Detection for Holistic Scene Understanding,
ACIVS11(736-747).
Springer DOI 1108
BibRef

Varadarajan, K.M.[Karthik Mahesh], Vincze, M.[Markus],
AfNet: The Affordance Network,
ACCV12(I:512-523).
Springer DOI 1304
BibRef
Earlier:
Knowledge Representation and Inference for Grasp Affordances,
CVS11(173-182).
Springer DOI 1109
BibRef
And:
Surface reconstruction for RGB-D data using real-time depth propagation,
Dense11(723-724).
IEEE DOI 1201
BibRef
Earlier:
Real-time depth diffusion for 3D surface reconstruction,
ICIP10(4149-4152).
IEEE DOI 1009
BibRef

Olufs, S.[Sven], Vincze, M.[Markus],
Room-structure estimation in Manhattan-like environments from dense 2˝D range data using minumum entropy and histograms,
WACV11(118-124).
IEEE DOI 1101
BibRef

Richtsfeld, M.[Mario], Vincze, M.[Markus],
Point Cloud Segmentation Based on Radial Reflection,
CAIP09(955-962).
Springer DOI 0909
BibRef

He, B.[Bei], Wang, G.J.[Gui-Jin], Zhang, C.[Cha],
Iterative transductive learning for automatic image segmentation and matting with RGB-D data,
JVCIR(25), No. 5, 2014, pp. 1031-1043.
Elsevier DOI 1406
Image matting BibRef

Camplani, M.[Massimo], del Blanco, C.R.[Carlos Roberto], Salgado, L.[Luis], Jaureguizar, F.[Fernando], García, N.[Narciso],
Advanced background modeling with RGB-D sensors through classifiers combination and inter-frame foreground prediction,
MVA(25), No. 5, July 2014, pp. 1197-1210.
Springer DOI 1407
BibRef

Camplani, M.[Massimo], Salgado, L.[Luis],
Background foreground segmentation with RGB-D Kinect data: An efficient combination of classifiers,
JVCIR(25), No. 1, 2014, pp. 122-136.
Elsevier DOI 1502
RGB-D cameras BibRef

Camplani, M.[Massimo], del Blanco, C.R.[Carlos R.], Salgado, L.[Luis], Jaureguizar, F.[Fernando], García, N.[Narciso],
Multi-sensor background subtraction by fusing multiple region-based probabilistic classifiers,
PRL(50), No. 1, 2014, pp. 23-33.
Elsevier DOI 1410
Region-based background modeling BibRef

Husain, F., Dellen, B., Torras, C.,
Consistent Depth Video Segmentation Using Adaptive Surface Models,
Cyber(45), No. 2, February 2015, pp. 266-278.
IEEE DOI 1502
image segmentation BibRef

Abramov, A.[Alexey], Pauwels, K.[Karl], Papon, J.[Jeremie], Worgotter, F.[Florentin], Dellen, B.[Babette],
Depth-supported real-time video segmentation with the Kinect,
WACV12(457-464).
IEEE DOI 1203
Depth aided. BibRef

Yang, J., Gan, Z., Li, K., Hou, C.,
Graph-Based Segmentation for RGB-D Data Using 3-D Geometry Enhanced Superpixels,
Cyber(45), No. 5, May 2015, pp. 913-926.
IEEE DOI 1505
Color BibRef

Wang, A.[Anran], Lu, J.W.[Ji-Wen], Cai, J.F.[Jian-Fei], Wang, G.[Gang], Cham, T.J.[Tat-Jen],
Unsupervised Joint Feature Learning and Encoding for RGB-D Scene Labeling,
IP(24), No. 11, November 2015, pp. 4459-4473.
IEEE DOI 1509
BibRef
Earlier: A1, A2, A4, A3, A5:
Multi-modal Unsupervised Feature Learning for RGB-D Scene Labeling,
ECCV14(V: 453-467).
Springer DOI 1408
image coding BibRef

Wang, A.[Anran], Cai, J.F.[Jian-Fei], Lu, J.W.[Ji-Wen], Cham, T.J.[Tat-Jen],
Modality and Component Aware Feature Fusion for RGB-D Scene Classification,
CVPR16(5995-6004)
IEEE DOI 1612
BibRef
Earlier:
MMSS: Multi-modal Sharable and Specific Feature Learning for RGB-D Object Recognition,
ICCV15(1125-1133)
IEEE DOI 1602
Computer vision BibRef

Wang, A.[Anran], Lu, J.W.[Ji-Wen], Cai, J.F.[Jian-Fei], Cham, T.J.[Tat-Jen], Wang, G.[Gang],
Large-Margin Multi-Modal Deep Learning for RGB-D Object Recognition,
MultMed(17), No. 11, November 2015, pp. 1887-1898.
IEEE DOI 1511
Correlation BibRef

Tang, J., Jin, L., Li, Z., Gao, S.,
RGB-D Object Recognition via Incorporating Latent Data Structure and Prior Knowledge,
MultMed(17), No. 11, November 2015, pp. 1899-1908.
IEEE DOI 1511
Data structures BibRef

Fehr, D.[Duc], Beksi, W.J.[William J.], Zermas, D.[Dimitris], Papanikolopoulos, N.[Nikolaos],
Covariance based point cloud descriptors for object detection and recognition,
CVIU(142), No. 1, 2016, pp. 80-93.
Elsevier DOI 1512
RGB-D data BibRef

Stückler, J.[Jörg], Waldvogel, B.[Benedikt], Schulz, H.[Hannes], Behnke, S.[Sven],
Dense real-time mapping of object-class semantics from RGB-D video,
RealTimeIP(10), No. 4, December 2015, pp. 599-609.
Springer DOI 1512
BibRef

Sanchez-Riera, J.[Jordi], Hua, K.L.[Kai-Lung], Hsiao, Y.S.[Yuan-Sheng], Lim, T.[Tekoing], Hidayati, S.C.[Shintami C.], Cheng, W.H.[Wen-Huang],
A comparative study of data fusion for RGB-D based visual recognition,
PRL(73), No. 1, 2016, pp. 1-6.
Elsevier DOI 1604
RGB-D BibRef

Ahmed, N.[Naveed], Khalifa, S.[Salam],
Time-coherent 3D animation reconstruction from RGB-D video,
SIViP(10), No. 4, April 2016, pp. 783-790.
Springer DOI 1604
BibRef

Thřgersen, M.[Mikkel], Escalera, S.[Sergio], Gonzŕlez, J.[Jordi], Moeslund, T.B.[Thomas B.],
Segmentation of RGB-D indoor scenes by stacking random forests and conditional random fields,
PRL(80), No. 1, 2016, pp. 208-215.
Elsevier DOI 1609
RGB-D sematic segmentation BibRef

Hasnat, M.A.[M. Abul], Alata, O.[Olivier], Trémeau, A.[Alain],
Joint Color-Spatial-Directional Clustering and Region Merging (JCSD-RM) for Unsupervised RGB-D Image Segmentation,
PAMI(38), No. 11, November 2016, pp. 2255-2268.
IEEE DOI 1610
BibRef
Earlier:
Unsupervised Clustering of Depth Images Using Watson Mixture Model,
ICPR14(214-219)
IEEE DOI 1412
BibRef
Earlier:
Unsupervised RGB-D image segmentation using joint clustering and region merging,
BMVC14(xx-yy).
HTML Version. 1410
Clustering methods BibRef

Li, X.[Xiao], Fang, M.[Min], Zhang, J.J.[Ju-Jie], Wu, J.Q.[Jin-Qiao],
Learning Coupled Classifiers with RGB images for RGB-D object recognition,
PR(61), No. 1, 2017, pp. 433-446.
Elsevier DOI 1609
Object recognition BibRef

Ibańez, R.[Rodrigo], Soria, Á.[Álvaro], Teyseyre, A.[Alfredo], Rodríguez, G.[Guillermo], Campo, M.[Marcelo],
Approximate string matching: A lightweight approach to recognize gestures with Kinect,
PR(62), No. 1, 2017, pp. 73-86.
Elsevier DOI 1609
Natural user interfaces BibRef

Deng, Z.[Zhuo], Todorovic, S.[Sinisa], Latecki, L.J.[Longin Jan],
Unsupervised object region proposals for RGB-D indoor scenes,
CVIU(154), No. 1, 2017, pp. 127-136.
Elsevier DOI 1612
BibRef
Earlier: A1, A3, Only:
Unsupervised Segmentation of RGB-D Images,
ACCV14(III: 423-435).
Springer DOI 1504
Object segmentation BibRef

Song, H., Liu, Z., Xie, Y., Wu, L., Huang, M.,
RGBD Co-saliency Detection via Bagging-Based Clustering,
SPLetters(23), No. 12, December 2016, pp. 1722-1726.
IEEE DOI 1612
feature extraction BibRef


Peng, H.[Houwen], Li, B.[Bing], Xiong, W.H.[Wei-Hua], Hu, W.M.[Wei-Ming], Ji, R.R.[Rong-Rong],
RGBD Salient Object Detection: A Benchmark and Algorithms,
ECCV14(III: 92-109).
Springer DOI 1408
BibRef

Hou, S.H.[Sai-Hui], Wang, Z.L.[Zi-Lei], Wu, F.[Feng],
Deeply Exploit Depth Information for Object Detection,
Robust16(1092-1100)
IEEE DOI 1612
BibRef

Ren, Z.[Zhile], Sudderth, E.B.[Erik B.],
Three-Dimensional Object Detection and Layout Prediction Using Clouds of Oriented Gradients,
CVPR16(1525-1533)
IEEE DOI 1612
BibRef

Feng, D., Barnes, N.[Nick], You, S., McCarthy, C.[Chris],
Local Background Enclosure for RGB-D Salient Object Detection,
CVPR16(2343-2350)
IEEE DOI 1612
BibRef

Liu, C.[Chen], Kohli, P.[Pushmeet], Furukawa, Y.[Yasutaka],
Layered Scene Decomposition via the Occlusion-CRF,
CVPR16(165-173)
IEEE DOI 1612
BibRef

de Gregorio, D.[Daniele], Tombari, F.[Federico], di Stefano, L.[Luigi],
RobotFusion: Grasping with a Robotic Manipulator via Multi-view Reconstruction,
6DPose16(III: 634-647).
Springer DOI 1611
BibRef

Sharma, A.[Abhishek], Grau, O.[Oliver], Fritz, M.[Mario],
VConv-DAE: Deep Volumetric Shape Learning Without Object Labels,
DeepLearn16(III: 236-250).
Springer DOI 1611
BibRef

Slavcheva, M.[Miroslava], Kehl, W.[Wadim], Navab, N.[Nassir], Ilic, S.[Slobodan],
SDF-2-SDF: Highly Accurate 3D Object Reconstruction,
ECCV16(I: 680-696).
Springer DOI 1611
3D from RGB-D BibRef

Tzionas, D.[Dimitrios], Gall, J.[Juergen],
Reconstructing Articulated Rigged Models from RGB-D Videos,
6DPose16(III: 620-633).
Springer DOI 1611
BibRef

Wang, J.H.[Jing-Hua], Wang, Z.H.[Zhen-Hua], Tao, D.C.[Da-Cheng], See, S.[Simon], Wang, G.[Gang],
Learning Common and Specific Features for RGB-D Semantic Segmentation with Deconvolutional Networks,
ECCV16(V: 664-679).
Springer DOI 1611
BibRef

Liu, X.D.[Xin-Da], Wang, X.M.[Xue-Ming], Jiang, S.Q.[Shu-Qiang],
RGB-D scene classification via heterogeneous model fusion,
ICIP16(499-503)
IEEE DOI 1610
Boolean functions BibRef

Yun, J.S., Sim, J.Y.,
Supervoxel-based saliency detection for large-scale colored 3D point clouds,
ICIP16(4062-4066)
IEEE DOI 1610
Clustering algorithms BibRef

Feng, J.[Jie], Wang, Y.[Yan], Chang, S.F.[Shih-Fu],
3D shape retrieval using a single depth image from low-cost sensors,
WACV16(1-9)
IEEE DOI 1606
Computational modeling. RGB-D sensors. BibRef

Tang, B., Zhou, Y., Yu, Y., Du, S.,
Higher-order class-specific priors for semantic segmentation of 3D outdoor scenes,
WACV16(1-9)
IEEE DOI 1606
Analytical models BibRef

Liu, S., Li, W., Ogunbona, P., Chow, Y.W.,
Creating Simplified 3D Models with High Quality Textures,
DICTA15(1-8)
IEEE DOI 1603
RGB-D data. BibRef

Zaki, H.F.M., Shafait, F., Mian, A.,
Localized Deep Extreme Learning Machines for Efficient RGB-D Object Recognition,
DICTA15(1-8)
IEEE DOI 1603
image classification BibRef

Wetherall, J., Taylor, M., Hurley-Smith, D.,
Investigation into the effects of transmission-channel fidelity loss in RGBD sensor data for SLAM,
WSSIP15(81-84)
IEEE DOI 1603
SLAM (robots) BibRef

Fooladgar, F., Kasaei, S.,
Semantic Segmentation of RGB-D Images Using 3D and Local Neighbouring Features,
DICTA15(1-7)
IEEE DOI 1603
computer vision BibRef

Pham, T.T.[Trung T.], Reid, I.D.[Ian D.], Latif, Y.[Yasir], Gould, S.[Stephen],
Hierarchical Higher-Order Regression Forest Fields: An Application to 3D Indoor Scene Labelling,
ICCV15(2246-2254)
IEEE DOI 1602
RGB-D. Computational modeling BibRef

Cheng, Y., Cai, R., Zhang, C., Li, Z., Zhao, X., Huang, K., Rui, Y.,
Query Adaptive Similarity Measure for RGB-D Object Recognition,
ICCV15(145-153)
IEEE DOI 1602
Art BibRef

Hachama, M., Ghanem, B., Wonka, P.,
Intrinsic Scene Decomposition from RGB-D Images,
ICCV15(810-818)
IEEE DOI 1602
Coherence BibRef

Chandra, S.[Siddhartha], Chrysos, G.G.[Grigorios G.], Kokkinos, I.[Iasonas],
Surface Based Object Detection in RGBD Images,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Soni, N.[Nishit], Namboodiri, A.M.[Anoop M.], Jawahar, C.V., Ramalingam, S.[Srikumar],
Semantic Classification of Boundaries of an RGBD Image,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Liu, J.[Jing], Ren, T.[Tongwei], Bei, J.[Jia],
Elastic Edge Boxes for Object Proposal on RGB-D Images,
MMMod16(I: 199-211).
Springer DOI 1601
BibRef

Xue, H.Y.[Hao-Yang], Gu, Y.[Yun], Li, Y.J.[Yi-Jun], Yang, J.[Jie],
RGB-D saliency detection via mutual guided manifold ranking,
ICIP15(666-670)
IEEE DOI 1512
Depth map cues; Mutual guided manifold ranking; Saliency detection BibRef

Petrelli, A.[Alioscia], Pau, D.[Danilo], di Stefano, L.[Luigi],
Analysis of Compact Features for RGB-D Visual Search,
CIAP15(II:14-24).
Springer DOI 1511
BibRef

Geiger, A.[Andreas], Wang, C.[Chaohui],
Joint 3D Object and Layout Inference from a Single RGB-D Image,
GCPR15(183-195).
Springer DOI 1511
BibRef

Nakaguro, Y.[Yoichi], Qureshi, W.S.[Waqar S.], Dailey, M.N.[Matthew N.], Ekpanyapong, M.[Mongkol], Bunnun, P.[Pished], Tungpimolrut, K.[Kanokvate],
Volumetric 3D Reconstruction and Parametric Shape Modeling from RGB-D Sequences,
CIAP15(I:500-516).
Springer DOI 1511
BibRef

Zhu, C.[Chen], Bilgeri, S.[Simon], Günther, C.[Christoph],
Spatial Uncertainty Model of a Three-View RGB-D Camera System,
ISVC14(II: 117-128).
Springer DOI 1501
Combine 2 view stereo with RBG-D for more complete modeling. BibRef

Fu, H.Z.[Hua-Zhu], Xu, D.[Dong], Lin, S.[Stephen], Liu, J.[Jiang],
Object-based RGBD image co-segmentation with mutex constraint,
CVPR15(4428-4436)
IEEE DOI 1510
BibRef

Banica, D.[Dan], Sminchisescu, C.[Cristian],
Second-order constrained parametric proposals and sequential search-based structured prediction for semantic segmentation in RGB-D images,
CVPR15(3517-3526)
IEEE DOI 1510
BibRef

Cinque, L.[Luigi], Danani, A.[Alessandro], Dondi, P.[Piercarlo], Lombardi, L.[Luca],
Real-Time Foreground Segmentation with Kinect Sensor,
CIAP15(II:56-65).
Springer DOI 1511
BibRef

Wan, S.H.[Shao-Hua], Aggarwal, J.K.,
Robust object recognition in RGB-D egocentric videos based on Sparse Affine Hull Kernel,
PBVS15(97-104)
IEEE DOI 1510
Cameras BibRef

Ren, J.[Jianqiang], Gong, X.J.[Xiao-Jin], Yu, L.[Lu], Zhou, W.H.[Wen-Hui], Yang, M.Y.[Michael Ying],
Exploiting global priors for RGB-D saliency detection,
FusionDynamic15(25-32)
IEEE DOI 1510
Image color analysis BibRef

Liu, W.[Wei], Ji, R.R.[Rong-Rong], Li, S.[Shaozi],
Towards 3D object detection with bimodal deep Boltzmann machines over RGBD imagery,
CVPR15(3013-3021)
IEEE DOI 1510
BibRef

Diebold, J.[Julia], Demmel, N.[Nikolaus], Hazirbas, C.[Caner], Moeller, M.[Michael], Cremers, D.[Daniel],
Interactive Multi-label Segmentation of RGB-D Images,
SSVM15(294-306).
Springer DOI 1506
BibRef

Nghiem, A.T.[Anh-Tuan], Bremond, F.[Francois],
Background subtraction in people detection framework for RGB-D cameras,
AVSS14(241-246)
IEEE DOI 1411
Cameras BibRef

Trabelsi, R.[Rim], Smach, F.[Fethi], Jabri, I.[Issam], Bouallegue, A.[Ammar],
Multimodal Background Modeling Using RGB-Depth Features,
CIARP14(884-892).
Springer DOI 1411
BibRef

Hickson, S.[Steven], Essa, I.[Irfan], Christensen, H.[Henrik],
Semantic Instance Labeling Leveraging Hierarchical Segmentation,
WACV15(1068-1075)
IEEE DOI 1503
Accuracy BibRef

Hickson, S.[Steven], Birchfield, S.[Stan], Essa, I.[Irfan], Christensen, H.[Henrik],
Efficient Hierarchical Graph-Based Segmentation of RGBD Videos,
CVPR14(344-351)
IEEE DOI 1409
4D Segmentation BibRef

Barrera, F.[Fernando], Padoy, N.[Nicolas],
Piecewise Planar Decomposition of 3D Point Clouds Obtained from Multiple Static RGB-D Cameras,
3DV14(194-201)
IEEE DOI 1503
Cameras BibRef

Lim, H.[Hyon], Lim, J.W.[Jong-Woo], Kim, H.J.[H. Jin],
Online 3D Reconstruction and 6-DoF Pose Estimation for RGB-D Sensors,
CVVT14(238-254).
Springer DOI 1504
BibRef

Zhang, Q.S.[Quan-Shi], Song, X.[Xuan], Shao, X.W.[Xiao-Wei], Zhao, H.J.[Hui-Jing], Shibasaki, R.[Ryosuke],
When 3D Reconstruction Meets Ubiquitous RGB-D Images,
CVPR14(700-707)
IEEE DOI 1409
3D reconstruction. Using category models. Rotation, 3D and texture. BibRef

Kerl, C.[Christian], Souiai, M.[Mohamed], Sturm, J.[Jurgen], Cremers, D.[Daniel],
Towards Illumination-Invariant 3D Reconstruction Using ToF RGB-D Cameras,
3DV14(39-46)
IEEE DOI 1503
Cameras BibRef

Perera, S.[Samunda], Barnes, N.[Nick],
1-Point Rigid Motion Estimation and Segmentation with a RGB-D Camera,
DICTA13(1-8)
IEEE DOI 1402
BibRef
Earlier:
Maximal Cliques Based Rigid Body Motion Segmentation with a RGB-D Camera,
ACCV12(II:120-133).
Springer DOI 1304
BibRef
Earlier:
A Simple and Practical Solution to the Rigid Body Motion Segmentation Problem Using a RGB-D Camera,
DICTA11(494-500).
IEEE DOI 1205
cameras BibRef

Steinbrucker, F.[Frank], Kerl, C.[Christian], Cremers, D.[Daniel],
Large-Scale Multi-resolution Surface Reconstruction from RGB-D Sequences,
ICCV13(3264-3271)
IEEE DOI 1403
BibRef

Weikersdorfer, D.[David], Schick, A.[Alexander], Cremers, D.[Daniel],
Depth-adaptive supervoxels for RGB-D video segmentation,
ICIP13(2708-2712)
IEEE DOI 1402
RGB-D; Superpixels; Supervoxels; Video Analysis; Video Segmentation BibRef

Guan, L.[Li], Yu, T.[Ting], Tu, P.[Peter], Lim, S.N.[Ser-Nam],
Simultaneous image segmentation and 3D plane fitting for RGB-D sensors: An iterative framework,
PCP12(49-56).
IEEE DOI 1207
BibRef

Srinivasan, N.[Natesh], Dellaert, F.[Frank],
A Rao-Blackwellized MCMC algorithm for recovering piecewise planar 3D models from multiple view RGBD images,
ICIP14(5392-5392)
IEEE DOI 1502
Bayes methods BibRef

Dellaert, F.[Frank],
Factor Graphs for Fast and Scalable 3D Reconstruction and Mapping,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Erdogan, C.[Can], Paluri, M.[Manohar], Dellaert, F.[Frank],
Planar Segmentation of RGBD Images Using Fast Linear Fitting and Markov Chain Monte Carlo,
CRV12(32-39).
IEEE DOI 1207
BibRef

Weikersdorfer, D.[David], Gossow, D.[David], Beetz, M.[Michael],
Depth-adaptive superpixels,
ICPR12(2087-2090).
WWW Link. 1302
BibRef

Kim, B.S.[Byung-Soo], Kohli, P.[Pushmeet], Savarese, S.[Silvio],
3D Scene Understanding by Voxel-CRF,
ICCV13(1425-1432)
IEEE DOI 1403
3D reconstruction; RGB-D; Scene understanding BibRef

Sallem, N.K.[Nizar K.], Devy, M.[Michel],
Extended GrabCut for 3D and RGB-D Point Clouds,
ACIVS13(354-365).
Springer DOI 1311
BibRef

Specht, A.R., Devy, M.,
Surface segmentation using a modified ball-pivoting algorithm,
ICIP04(III: 1931-1934).
IEEE DOI 0505
BibRef

Sappa, A.D., Devy, M.,
Fast range image segmentation by an edge detection strategy,
3DIM01(292-299).
IEEE DOI 0106
BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
The Facet Model for Descriptions .


Last update:Jan 11, 2017 at 16:41:39