21.4.2.3.2 Depth Based, Stereo, Hand Pose, Hand Posture, Hand Shape

Chapter Contents (Back)
Hand Pose. Hand Posture. Depth. See also Hand Pose, Hand Posture, Hand Shape.

Liang, H.[Hui], Yuan, J.S.[Jun-Song], Thalmann, D.,
Parsing the Hand in Depth Images,
MultMed(16), No. 5, August 2014, pp. 1241-1253.
IEEE DOI 1410
Markov processes BibRef

Ge, L.H.[Liu-Hao], Liang, H.[Hui], Yuan, J.S.[Jun-Song], Thalmann, D.[Daniel],
Robust 3D Hand Pose Estimation From Single Depth Images Using Multi-View CNNs,
IP(27), No. 9, September 2018, pp. 4422-4436.
IEEE DOI 1807
BibRef
Earlier:
3D Convolutional Neural Networks for Efficient and Robust Hand Pose Estimation from Single Depth Images,
CVPR17(5679-5688)
IEEE DOI 1711
BibRef
Earlier:
Robust 3D Hand Pose Estimation in Single Depth Images: From Single-View CNN to Multi-View CNNs,
CVPR16(3593-3601)
IEEE DOI 1612
neural nets, pose estimation, probability, regression analysis, articulated hand pose estimation, depth information, multi-view CNNs. Feature extraction, Real-time systems, Robustness, Solid modeling, BibRef

Ge, L.H.[Liu-Hao], Liang, H.[Hui], Yuan, J.S.[Jun-Song], Thalmann, D.[Daniel],
Real-Time 3D Hand Pose Estimation with 3D Convolutional Neural Networks,
PAMI(41), No. 4, April 2019, pp. 956-970.
IEEE DOI 1903
Pose estimation, Feature extraction, Solid modeling, deep learning BibRef

Xu, C.[Chi], Nanjappa, A.[Ashwin], Zhang, X.[Xiaowei], Cheng, L.[Li],
Estimate Hand Poses Efficiently from Single Depth Images,
IJCV(116), No. 1, January 2016, pp. 21-45.
Springer DOI 1601
BibRef

Xu, C.[Chi], Govindarajan, L.N.[Lakshmi Narasimhan], Zhang, Y.[Yu], Stewart, J.[James], Bichler, Z.[Zoë], Jesuthasan, S.[Suresh], Claridge-Chang, A.[Adam], Mathuru, A.S.[Ajay Sriram], Tang, W.L.[Wen-Long], Zhu, P.[Peixin], Cheng, L.[Li],
Lie-X: Depth Image Based Articulated Object Pose Estimation, Tracking, and Action Recognition on Lie Groups,
IJCV(123), No. 3, July 2017, pp. 454-478.
Springer DOI 1706
BibRef
And: Author List Corrected: IJCV(126), No. 8, August 2018, pp. 897.
Springer DOI 1807
BibRef

Supancic, III, J.S.[James Steven], Rogez, G.[Grégory], Yang, Y.[Yi], Shotton, J.[Jamie], Ramanan, D.[Deva],
Depth-Based Hand Pose Estimation: Methods, Data, and Challenges,
IJCV(126), No. 11, November 2018, pp. 1180-1198.
Springer DOI 1809
BibRef
Earlier:
Depth-Based Hand Pose Estimation: Data, Methods, and Challenges,
ICCV15(1868-1876)
IEEE DOI 1602
BibRef
Earlier: A2, A1, A5, Only:
Understanding Everyday Hands in Action from RGB-D Images,
ICCV15(3889-3897)
IEEE DOI 1602
Benchmark testing; Clutter; Data models; Training data. Cameras BibRef

Basaru, R.R.[Rilwan Remilekun], Child, C.[Chris], Alonso, E.[Eduardo], Slabaugh, G.[Gregory],
Data-driven recovery of hand depth using CRRF on stereo images,
IET-CV(12), No. 5, August 2018, pp. 666-678.
DOI Link 1807
BibRef

Gomez-Donoso, F.[Francisco], Orts-Escolano, S.[Sergio], Cazorla, M.[Miguel],
Large-scale multiview 3D hand pose dataset,
IVC(81), 2019, pp. 25-33.
Elsevier DOI 1902
3D hand pose, Multiview, Dataset, Deep learning BibRef

Wang, G.[Guijin], Chen, X.[Xinghao], Guo, H.[Hengkai], Zhang, C.[Cairong],
Region ensemble network: Towards good practices for deep 3D hand pose estimation,
JVCIR(55), 2018, pp. 404-414.
Elsevier DOI 1809
Convolutional network, Hand pose estimation, Human pose estimation, Fingertip detection, Ensemble learning, Depth imaging BibRef

Guo, H., Wang, G., Chen, X., Zhang, C., Qiao, F., Yang, H.,
Region ensemble network: Improving convolutional network for hand pose estimation,
ICIP17(4512-4516)
IEEE DOI 1803
Bagging, Computer vision, Convolution, Pose estimation, Testing, Training, Convolutional Network, Hand Pose Estimation BibRef

Wu, Y., Ji, W., Li, X., Wang, G., Yin, J., Wu, F.,
Context-Aware Deep Spatiotemporal Network for Hand Pose Estimation From Depth Images,
Cyber(50), No. 2, February 2020, pp. 787-797.
IEEE DOI 1912
Feature extraction, Pose estimation, Spatiotemporal phenomena, Image sequences, Context modeling, Adaptation models, Data mining, hand pose estimation BibRef

Oberweger, M.[Markus], Wohlhart, P.[Paul], Lepetit, V.[Vincent],
Generalized Feedback Loop for Joint Hand-Object Pose Estimation,
PAMI(42), No. 8, August 2020, pp. 1898-1912.
IEEE DOI 2007
BibRef
Earlier:
Training a Feedback Loop for Hand Pose Estimation,
ICCV15(3316-3324)
IEEE DOI 1602
Pose estimation, Solid modeling, Optimization, Feedback loop, Training data, Data models, hand-object manipulation BibRef

Oberweger, M., Riegler, G., Wohlhart, P., Lepetit, V.,
Efficiently Creating 3D Training Data for Fine Hand Pose Estimation,
CVPR16(4957-4965)
IEEE DOI 1612
Data models BibRef


Min, Y., Zhang, Y., Chai, X., Chen, X.,
An Efficient PointLSTM for Point Clouds Based Gesture Recognition,
CVPR20(5760-5769)
IEEE DOI 2008
Gesture recognition, Feature extraction, Task analysis, Data mining, Logic gates, Computer vision BibRef

Gu, J., Wang, Z., Ouyang, W., Zhang, W., Li, J., Zhuo, L.,
3D Hand Pose Estimation with Disentangled Cross-Modal Latent Space,
WACV20(380-389)
IEEE DOI 2006
Pose estimation, Task analysis, Solid modeling, Decoding BibRef

Chen, L., Lin, S., Xie, Y., Lin, Y., Fan, W., Xie, X.,
DGGAN: Depth-image Guided Generative Adversarial Networks for Disentangling RGB and Depth Images in 3D Hand Pose Estimation,
WACV20(400-408)
IEEE DOI 2006
Training, Image reconstruction, Pose estimation, Task analysis, Solid modeling BibRef

Zhu, T., Sun, Y., Ma, X., Lin, X.,
Hand Pose Ensemble Learning Based on Grouping Features of Hand Point Sets,
Hands19(2856-2865)
IEEE DOI 2004
feature extraction, feature selection, learning (artificial intelligence), pose estimation, Ensemble learning BibRef

Ge, L., Cai, Y., Weng, J., Yuan, J.,
Hand PointNet: 3D Hand Pose Estimation Using Point Sets,
CVPR18(8417-8426)
IEEE DOI 1812
Pose estimation, Feature extraction, Cameras, Neural networks, Sensitivity BibRef

Malik, J., Elhayek, A., Nunnari, F., Varanasi, K., Tamaddon, K., Heloir, A., Stricker, D.,
DeepHPS: End-to-end Estimation of 3D Hand Pose and Shape by Learning from Synthetic Depth,
3DV18(110-119)
IEEE DOI 1812
computer vision, image classification, image motion analysis, image segmentation, learning (artificial intelligence), convolutional neural networks BibRef

Baek, S., Kim, K.I., Kim, T.,
Augmented Skeleton Space Transfer for Depth-Based Hand Pose Estimation,
CVPR18(8330-8339)
IEEE DOI 1812
Skeleton, Shape, Training, Cameras, Pose estimation, Databases BibRef

Li, J., Wang, Z.,
Local Regression Based Hourglass Network for Hand Pose Estimation from a Single Depth Image,
ICPR18(1767-1772)
IEEE DOI 1812
Feature extraction, Task analysis, Pose estimation, Convolutional neural networks, Sensors BibRef

Yuan, S., Garcia-Hernando, G., Stenger, B., Moon, G., Chang, J.Y., Lee, K.M., Molchanov, P., Kautz, J., Honari, S., Ge, L., Yuan, J., Chen, X., Wang, G., Yang, F., Akiyama, K., Wu, Y., Wan, Q., Madadi, M., Escalera, S., Li, S., Lee, D., Oikonomidis, I., Argyros, A., Kim, T.,
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals,
CVPR18(2636-2645)
IEEE DOI 1812
Task analysis, Pose estimation, Joints, Training, Solid modeling BibRef

Wan, C., Probst, T., Van Gool, L.J., Yao, A.,
Dense 3D Regression for Hand Pose Estimation,
CVPR18(5147-5156)
IEEE DOI 1812
Pose estimation, Heating systems, Skeleton, Correlation BibRef

Zhou, Y.[Yidan], Lu, J.[Jian], Du, K.[Kuo], Lin, X.B.[Xiang-Bo], Sun, Y.[Yi], Ma, X.H.[Xiao-Hong],
HBE: Hand Branch Ensemble Network for Real-Time 3D Hand Pose Estimation,
ECCV18(XIV: 521-536).
Springer DOI 1810
BibRef

Ge, L.H.[Liu-Hao], Ren, Z.[Zhou], Yuan, J.S.[Jun-Song],
Point-to-Point Regression PointNet for 3D Hand Pose Estimation,
ECCV18(XIII: 489-505).
Springer DOI 1810
BibRef

Zhang, J., Jiao, J., Chen, M., Qu, L., Xu, X., Yang, Q.,
A hand pose tracking benchmark from stereo matching,
ICIP17(982-986)
IEEE DOI 1803
Benchmark testing, Cameras, Image color analysis, Image segmentation, Noise measurement, Skin, Training, stereo matching and hand pose tracking BibRef

Basaru, R.R., Child, C., Alonso, E., Slabaugh, G.,
Hand Pose Estimation Using Deep Stereovision and Markov-Chain Monte Carlo,
Hands17(595-603)
IEEE DOI 1802
Cameras, Computer vision, Monte Carlo methods, Pose estimation, Proposals, Robustness BibRef

Otberdout, N., Ballihi, L., Aboutajdine, D.,
Hand pose estimation based on deep learning depth map for hand gesture recognition,
ISCV17(1-8)
IEEE DOI 1710
Gesture recognition, Neural networks, Neurons, Pose estimation, Solid modeling, Three-dimensional, displays BibRef

Goudie, D., Galata, A.,
3D Hand-Object Pose Estimation from Depth with Convolutional Neural Networks,
FG17(406-413)
IEEE DOI 1707
Cost function, Image segmentation, Neural networks, Pose estimation, Sensors, Training BibRef

Madadi, M., Escalera, S., Carruesco, A., Andujar, C., Baró, X., Gonzŕlez, J.,
Occlusion Aware Hand Pose Recovery from Sequences of Depth Images,
FG17(230-237)
IEEE DOI 1707
Cameras, Computational modeling, Feature extraction, Pose estimation, Shape, Solid modeling, Three-dimensional, displays BibRef

Asad, M.[Muhammad], Gentet, E.[Enguerrand], Basaru, R.R.[Rilwan Remilekun], Slabaugh, G.[Greg],
Generatinga 3D hand model from frontal color and range scans,
ICIP15(4589-4593)
IEEE DOI 1512
Hand model; pose estimation; reconstruction BibRef

Guo, H., Wang, G., Chen, X.,
Two-stream convolutional neural network for accurate RGB-D fingertip detection using depth and edge information,
ICIP16(2608-2612)
IEEE DOI 1610
BibRef
And: A3, A2, A1:
Accurate fingertip detection from binocular mask images,
VCIP16(1-4)
IEEE DOI 1701
Image edge detection BibRef

Khamis, S.[Sameh], Taylor, J.[Jonathan], Shotton, J.[Jamie], Keskin, C.[Cem], Izadi, S.[Shahram], Fitzgibbon, A.[Andrew],
Learning an efficient model of hand shape variation from depth images,
CVPR15(2540-2548)
IEEE DOI 1510
BibRef

Fan, C.Y.[Chin-Yun], Lin, M.H.[Meng-Hsuan], Su, T.F.[Te-Feng], Lai, S.H.[Shang-Hong], Yu, C.H.[Chih-Hsiang],
3D hand skeleton model estimation from a depth image,
MVA15(489-492)
IEEE DOI 1507
Computational modeling BibRef

Sohn, M.K.[Myoung-Kyu], Kim, D.J.[Dong-Ju], Kim, H.[Hyunduk],
Hand Part Classification Using Single Depth Images,
UCCV14(253-261).
Springer DOI 1504
BibRef

Rogez, G.[Grégory], Khademi, M.[Maryam], Supancic, III, J.S., Montiel, J.M.M., Ramanan, D.[Deva],
3D Hand Pose Detection in Egocentric RGB-D Images,
CDC4CV14(356-371).
Springer DOI 1504
BibRef

Taylor, J.[Jonathan], Stebbing, R.[Richard], Ramakrishna, V.[Varun], Keskin, C.[Cem], Shotton, J.[Jamie], Izadi, S.[Shahram], Hertzmann, A.[Aaron], Fitzgibbon, A.[Andrew],
User-Specific Hand Modeling from Monocular Depth Sequences,
CVPR14(644-651)
IEEE DOI 1409
BibRef

Kang, B.[Byungkyu], Rodrigue, M., Hollerer, T., Lim, H.[Hwasup],
Real time hand pose recognition with depth sensors for mixed reality interfaces,
3DUI13(171-172)
IEEE DOI 1406
decision trees BibRef

Xu, C.[Chi], Cheng, L.[Li],
Efficient Hand Pose Estimation from a Single Depth Image,
ICCV13(3456-3462)
IEEE DOI 1403
hand pose estimation; random forest; realtime BibRef

Bagdanov, A.D.[Andrew D.], del Bimbo, A.[Alberto], Seidenari, L.[Lorenzo], Usai, L.[Lorenzo],
Real-time hand status recognition from RGB-D imagery,
ICPR12(2456-2459).
WWW Link. 1302
BibRef

Wang, Q.[Qi], Chen, X.[Xilin], Gao, W.[Wen],
Skin Color Weighted Disparity Competition for Hand Segmentation from Stereo Camera,
BMVC10(xx-yy).
HTML Version. 1009
BibRef

Tran, C.[Cuong], Trivedi, M.M.[Mohan M.],
Hand modeling and tracking from voxel data: An integrated framework with automatic initialization,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Delamarre, Q., Faugeras, O.D.,
Finding Pose of Hand in Video Images: A Stereo-Based Approach,
AFGR98(585-590).
IEEE DOI
PS File. BibRef 9800

Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Hand Tracking for Gestures .


Last update:Sep 14, 2020 at 15:32:18