Feature Extraction Using an RNN Autoencoder for Skeleton-Based Abnormal Gait Recognition
暂无分享,去创建一个
Kyoobin Lee | Kooksung Jun | Deok-Won Lee | Sanghyub Lee | Mun Sang Kim | Kyoobin Lee | Sanghyub Lee | M. Kim | Kooksung Jun | Deok-Won Lee
[1] Kingshuk Chakravarty,et al. Person Identification using Skeleton Information from Kinect , 2013, ACHI 2013.
[2] Melvyn Roerdink,et al. Kinematic Validation of a Multi-Kinect v2 Instrumented 10-Meter Walkway for Quantitative Gait Assessments , 2015, PloS one.
[3] Shuicheng Yan,et al. Robust LSTM-Autoencoders for Face De-Occlusion in the Wild , 2016, IEEE Transactions on Image Processing.
[4] Wei Jiang,et al. Fault diagnosis of rolling bearings with recurrent neural network-based autoencoders. , 2018, ISA transactions.
[5] Jean Meunier,et al. Applying adversarial auto-encoder for estimating human walking gait abnormality index , 2019, Pattern Analysis and Applications.
[6] Marjorie Skubic,et al. Unobtrusive, Continuous, In-Home Gait Measurement Using the Microsoft Kinect , 2013, IEEE Transactions on Biomedical Engineering.
[7] Yuan Yan Tang,et al. Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images , 2019, IEEE Transactions on Cybernetics.
[8] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[9] Maxine Eskénazi,et al. Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders , 2017, ACL.
[10] Ales Procházka,et al. Bayesian classification and analysis of gait disorders using image and depth sensors of Microsoft Kinect , 2015, Digit. Signal Process..
[11] Xu Xu,et al. Accuracy of the Microsoft Kinect for measuring gait parameters during treadmill walking. , 2015, Gait & posture.
[12] Sai Zhang,et al. Multi-source Learning for Skeleton -based Action Recognition Using Deep LSTM Networks , 2018, 2018 24th International Conference on Pattern Recognition (ICPR).
[13] Majid Mirmehdi,et al. Online quality assessment of human motion from skeleton data , 2014, BMVC.
[14] Raja Giryes,et al. Autoencoders , 2020, ArXiv.
[15] Geoffrey E. Hinton,et al. Speech recognition with deep recurrent neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[16] Franck Multon,et al. Detection of gait cycles in treadmill walking using a Kinect. , 2015, Gait & posture.
[17] Jean Meunier,et al. Skeleton-Based Abnormal Gait Detection , 2016, Sensors.
[18] Marco Grangetto,et al. Human Classification Using Gait Features , 2014, BIOMET.
[19] Christopher D. Manning,et al. Effective Approaches to Attention-based Neural Machine Translation , 2015, EMNLP.
[20] Yuhong Guo,et al. Domain Adaptation With Neural Embedding Matching , 2020, IEEE Transactions on Neural Networks and Learning Systems.
[21] Jean Meunier,et al. Estimating skeleton-based gait abnormality index by sparse deep auto-encoder , 2018, 2018 IEEE Seventh International Conference on Communications and Electronics (ICCE).
[22] Yuanyuan Zhang,et al. Real Time Gait Recognition System Based on Kinect Skeleton Feature , 2014, ACCV Workshops.
[23] Viorica Patraucean,et al. Spatio-temporal video autoencoder with differentiable memory , 2015, ArXiv.
[24] Alexei A. Morozov,et al. Normal and pathological gait classification LSTM model , 2019, Artif. Intell. Medicine.
[25] Claudia Linnhoff-Popien,et al. Gait Recognition with Kinect , 2012 .
[26] Hong Liu,et al. Spatial-Temporal Data Augmentation Based on LSTM Autoencoder Network for Skeleton-Based Human Action Recognition , 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).
[27] Martin Schätz,et al. Motion tracking and gait feature estimation for recognising Parkinson’s disease using MS Kinect , 2015, BioMedical Engineering OnLine.
[28] Yoshua Bengio,et al. On the Properties of Neural Machine Translation: Encoder–Decoder Approaches , 2014, SSST@EMNLP.
[29] Navdeep Jaitly,et al. Hybrid speech recognition with Deep Bidirectional LSTM , 2013, 2013 IEEE Workshop on Automatic Speech Recognition and Understanding.
[30] Christopher Joseph Pal,et al. Delving Deeper into Convolutional Networks for Learning Video Representations , 2015, ICLR.
[31] Jean Meunier,et al. Walking gait dataset : point clouds , skeletons and silhouettes Technical Report Number 1379 , 2018 .
[32] Yong Du,et al. Hierarchical recurrent neural network for skeleton based action recognition , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Gang Wang,et al. Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks , 2017, IEEE Transactions on Image Processing.
[34] Dimitris Kastaniotis,et al. A framework for gait-based recognition using Kinect , 2015, Pattern Recognit. Lett..
[35] Matthew J. Hausknecht,et al. Beyond short snippets: Deep networks for video classification , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[36] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[37] Erik Marchi,et al. A novel approach for automatic acoustic novelty detection using a denoising autoencoder with bidirectional LSTM neural networks , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[38] Jaume Bacardit,et al. A Combined Deep Learning GRU-Autoencoder for the Early Detection of Respiratory Disease in Pigs Using Multiple Environmental Sensors , 2018, Sensors.
[39] Yoshua Bengio,et al. Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling , 2014, ArXiv.
[40] Hassen Drira,et al. Detection of Abnormal Gait from Skeleton Data , 2016, VISIGRAPP.
[41] Nitish Srivastava,et al. Unsupervised Learning of Video Representations using LSTMs , 2015, ICML.
[42] Alexandros André Chaaraoui,et al. Abnormal gait detection with RGB-D devices using joint motion history features , 2015, 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).
[43] Daniel Jurafsky,et al. A Hierarchical Neural Autoencoder for Paragraphs and Documents , 2015, ACL.
[44] Ennio Gambi,et al. Kinect as a Tool for Gait Analysis: Validation of a Real-Time Joint Extraction Algorithm Working in Side View , 2015, Sensors.
[45] Sepp Hochreiter,et al. The Vanishing Gradient Problem During Learning Recurrent Neural Nets and Problem Solutions , 1998, Int. J. Uncertain. Fuzziness Knowl. Based Syst..
[46] Ran Gilad-Bachrach,et al. Full body gait analysis with Kinect , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[47] Changhe Tu,et al. Classification of gait anomalies from kinect , 2018, The Visual Computer.
[48] Fathi M. Salem,et al. Gate-variants of Gated Recurrent Unit (GRU) neural networks , 2017, 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS).