21.4.2.3.1 Multi-Modal Gesture Recognition, Multimodal Recognition

Chapter Contents (Back)
Application, Gesture. Hand Gestures. Gesture. Multi-Modal Recogniton.

Djeraba, C.[Chaabane], Lablack, A.[Adel], Benabbas, Y.[Yassine],
Multi-Modal User Interactions in Controlled Environments,
Springer2010, ISBN: 978-1-4419-0315-0
WWW Link. Buy this book: Multi-Modal User Interactions in Controlled Environments (Multimedia Systems and Applications) 1010
BibRef

Wu, D.[Di], Pigou, L., Kindermans, P.J., Le, N.D.H., Shao, L.[Ling], Dambre, J., Odobez, J.M.,
Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition,
PAMI(38), No. 8, August 2016, pp. 1583-1597.
IEEE DOI 1608
feature extraction BibRef

Wu, D.[Di], Shao, L.[Ling],
Deep Dynamic Neural Networks for Gesture Segmentation and Recognition,
ChaLearn14(552-571).
Springer DOI 1504

See also Silhouette Analysis-Based Action Recognition Via Exploiting Human Poses. BibRef

Liu, L.[Li], Shao, L.[Ling],
Synthesis of spatio-temporal descriptors for dynamic hand gesture recognition using genetic programming,
FG13(1-7)
IEEE DOI 1309
genetic algorithms BibRef

Wu, D.[Di], Zhu, F.[Fan], Shao, L.[Ling],
One shot learning gesture recognition from RGBD images,
Gesture12(7-12).
IEEE DOI 1207
BibRef

Chang, J.Y.[Ju Yong],
Nonparametric Feature Matching Based Conditional Random Fields for Gesture Recognition from Multi-Modal Video,
PAMI(38), No. 8, August 2016, pp. 1612-1625.
IEEE DOI 1608
BibRef
Earlier:
Nonparametric Gesture Labeling from Multi-modal Data,
ChaLearn14(503-517).
Springer DOI 1504
dynamic programming BibRef

Neverova, N.[Natalia], Wolf, C.[Christian], Taylor, G.W.[Graham W.], Nebout, F.[Florian],
ModDrop: Adaptive Multi-Modal Gesture Recognition,
PAMI(38), No. 8, August 2016, pp. 1692-1706.
IEEE DOI 1608
BibRef
Earlier:
Multi-scale Deep Learning for Gesture Detection and Localization,
ChaLearn14(474-490).
Springer DOI 1504
audio streaming BibRef

Li, F., Neverova, N.[Natalia], Wolf, C.[Christian], Taylor, G.W.[Graham W.],
Modout: Learning Multi-Modal Architectures by Stochastic Regularization,
FG17(422-429)
IEEE DOI 1707
Backpropagation, Correlation, Fuses, Gesture recognition, Machine learning, Stochastic processes, Training BibRef

Neverova, N.[Natalia], Wolf, C.[Christian], Paci, G., Sommavilla, G., Taylor, G.W.[Graham W.], Nebout, F.,
A Multi-scale Approach to Gesture Detection and Recognition,
HACI13(484-491)
IEEE DOI 1403
gesture recognition BibRef

Joshi, A.[Ajjen], Monnier, C.[Camille], Betke, M.[Margrit], Sclaroff, S.[Stan],
Comparing random forest approaches to segmenting and classifying gestures,
IVC(58), No. 1, 2017, pp. 86-95.
Elsevier DOI 1703
BibRef
Earlier:
A random forest approach to segmenting and classifying gestures,
FG15(1-7)
IEEE DOI 1508
Gesture spotting. gesture recognition BibRef

Joshi, A.[Ajjen], Ghosh, S., Gunnery, S., Tickle-Degnen, L., Sclaroff, S.[Stan], Betke, M.[Margrit],
Context-Sensitive Prediction of Facial Expressivity Using Multimodal Hierarchical Bayesian Neural Networks,
FG18(278-285)
IEEE DOI 1806
Adaptation models, Bayes methods, Context modeling, Face, Feature extraction, Interviews, Neural networks, personalization BibRef

Joshi, A.[Ajjen], Ghosh, S., Betke, M.[Margrit], Sclaroff, S.[Stan], Pfister, H.,
Personalizing Gesture Recognition Using Hierarchical Bayesian Neural Networks,
CVPR17(455-464)
IEEE DOI 1711
Adaptation models, Bayes methods, Gesture recognition, Hidden Markov models, Neural networks, Stochastic, processes BibRef

Deng, M.W.[Min-Wei],
Robust human gesture recognition by leveraging multi-scale feature fusion,
SP:IC(83), 2020, pp. 115768.
Elsevier DOI 2003
Gesture recognition, Faster R-CNN, Feature extraction, Human-computer interaction BibRef

Cabrera-Quiros, L., Tax, D.M.J., Hung, H.,
Gestures In-The-Wild: Detecting Conversational Hand Gestures in Crowded Scenes Using a Multimodal Fusion of Bags of Video Trajectories and Body Worn Acceleration,
MultMed(22), No. 1, January 2020, pp. 138-147.
IEEE DOI 2001
Trajectory, Acceleration, Gesture recognition, Noise measurement, Human computer interaction, Visualization, Feature extraction, wearable acceleration BibRef

Yu, Z.T.[Zi-Tong], Zhou, B.J.[Ben-Jia], Wan, J.[Jun], Wang, P.[Pichao], Chen, H.Y.[Hao-Yu], Liu, X.[Xin], Li, S.Z.[Stan Z.], Zhao, G.Y.[Guo-Ying],
Searching Multi-Rate and Multi-Modal Temporal Enhanced Networks for Gesture Recognition,
IP(30), 2021, pp. 5626-5640.
IEEE DOI 2106
Gesture recognition, Convolution, Computer architecture, Task analysis, Benchmark testing, RGB-D gesture recognition BibRef

Gammulle, H.[Harshala], Denman, S.[Simon], Sridharan, S.[Sridha], Fookes, C.[Clinton],
TMMF: Temporal Multi-Modal Fusion for Single-Stage Continuous Gesture Recognition,
IP(30), 2021, pp. 7689-7701.
IEEE DOI 2109
Gesture recognition, Feature extraction, Solid modeling, Streaming media, Semantics, Visualization, temporal convolution networks BibRef


Gu, Y.[Yang], Li, Y.[Yajie], Chen, Y.[Yiqiang], Wang, J.[Jiwei], Shen, J.F.[Jian-Fei],
A Collaborative Multi-modal Fusion Method Based on Random Variational Information Bottleneck for Gesture Recognition,
MMMod21(I:62-74).
Springer DOI 2106
BibRef

Zhou, Y., Habermann, M., Xu, W., Habibie, I., Theobalt, C., Xu, F.,
Monocular Real-Time Hand Shape and Motion Capture Using Multi-Modal Data,
CVPR20(5345-5354)
IEEE DOI 2008
Feature extraction, Heating systems, Detectors, Kinematics, Predictive models BibRef

Li, D., Chen, Y., Gao, M., Jiang, S., Huang, C.,
Multimodal Gesture Recognition Using Densely Connected Convolution and BLSTM,
ICPR18(3365-3370)
IEEE DOI 1812
convolution, feature extraction, feedforward neural nets, gesture recognition, learning (artificial intelligence), Training BibRef

Miao, Q., Li, Y., Ouyang, W., Ma, Z., Xu, X., Shi, W., Cao, X.,
Multimodal Gesture Recognition Based on the ResC3D Network,
EmotionComp17(3047-3055)
IEEE DOI 1802
Correlation, Feature extraction, Gesture recognition, Hidden Markov models, Lighting, Videos BibRef

Wang, H.G.[Huo-Gen], Wang, P.C.[Pi-Chao], Song, Z.J.[Zhan-Jie], Li, W.Q.[Wan-Qing],
Large-Scale Multimodal Gesture Recognition Using Heterogeneous Networks,
EmotionComp17(3129-3137)
IEEE DOI 1802
Dynamics, Feature extraction, Gesture recognition, Machine learning, Spatiotemporal phenomena, Video sequences
See also Large-scale Continuous Gesture Recognition Using Convolutional Neural Networks. BibRef

Wang, H.G.[Huo-Gen], Wang, P.C.[Pi-Chao], Song, Z.J.[Zhan-Jie], Li, W.Q.[Wan-Qing],
Large-Scale Multimodal Gesture Segmentation and Recognition Based on Convolutional Neural Networks,
EmotionComp17(3138-3146)
IEEE DOI 1802
Dynamics, Feature extraction, Gesture recognition, Image segmentation, Motion segmentation, BibRef

Nishida, N.[Noriki], Nakayama, H.[Hideki],
Multimodal Gesture Recognition Using Multi-stream Recurrent Neural Network,
PSIVT15(682-694).
Springer DOI 1602
BibRef

Chen, G.[Guang], Clarke, D.[Daniel], Giuliani, M.[Manuel], Gaschler, A.[Andre], Wu, D.[Di], Weikersdorfer, D.[David], Knoll, A.[Alois],
Multi-modality Gesture Detection and Recognition with Un-supervision, Randomization and Discrimination,
ChaLearn14(608-622).
Springer DOI 1504
BibRef

Liang, B.[Bin], Zheng, L.[Lihong],
3D Motion Trail Model Based Pyramid Histograms of Oriented Gradient for Action Recognition,
ICPR14(1952-1957)
IEEE DOI 1412
BibRef
And:
Multi-modal Gesture Recognition Using Skeletal Joints and Motion Trail Model,
ChaLearn14(623-638).
Springer DOI 1504
BibRef
Earlier:
Three Dimensional Motion Trail Model for Gesture Recognition,
BD3DCV13(684-691)
IEEE DOI 1403
feature extraction BibRef

Fröhlich, C.[Christian], Biermann, P.[Peter], Latoschik, M.E.[Marc E.], Wachsmuth, I.[Ipke],
Processing Iconic Gestures in a Multimodal Virtual Construction Environment,
GW07(187-19).
Springer DOI 0705
BibRef

Trivedi, M.M.[Mohan M.], Huang, K.S.[Kohsia S.], Mikic, I.[Ivana],
Intelligent Environments and Active Camera Networks,
SMC-C00(xx-yy). Omnidirectional Vision, Panoramic Vision, Realtime Tracking, Intelligent Environments, Multicamera Systems,
PDF File.
PDF File. BibRef 0001

Trivedi, M.M.[Mohan M.], Mikic, I.[Ivana], Bhonsle, S.,
Active Camera Networks and Semantic Event Databases for Intelligent Environments,
ConferenceIEEE CVPR Workshop on Human Modeling, Analysis and Synthesis, Hilton Head, S.C. June 2000. Multicamera systems, intelligent environments.
PDF File.
PDF File. BibRef 0006

Huang, K.S.[Kohsia S.], Trivedi, M.M.,
3D Shape Context Based Gesture Analysis Integrated with Tracking using Omni Video Array,
VHCI05(III: 80-80).
IEEE DOI 0507
BibRef

Cheng, S.Y.[Shinko Y.], Trivedi, M.M.[Mohan M.],
Multimodal Voxelization and Kinematically Constrained Gaussian Mixture Models for Full Hand Pose Estimation: An Integrated Systems Approach,
CVS06(34).
IEEE DOI 0602
BibRef

LaViola, Jr., J.J.[Joseph J.],
A Multimodal Interface Framework for Using Hand Gestures and Speech in Virtual Environment Applications,
GW99(303).
Springer DOI 9903
BibRef

de Angeli, A.[Antonella], Wolff, F.[Fréderic], Romary, L.[Laurent], Gerbino, W.[Walter],
The Ecological Approach to Multimodal System Design,
GW99(49).
Springer DOI 9903
Understand gesture variability. BibRef

Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Hand Pose, Hand Posture, Hand Shape .


Last update:Nov 1, 2021 at 09:26:50