CNN-Based Multistage Gated Average Fusion (MGAF) for Human Action Recognition Using Depth and Inertial Sensors
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[1] Chalavadi Krishna Mohan,et al. Human Action Recognition Based on MOCAP Information Using Convolution Neural Networks , 2014, 2014 13th International Conference on Machine Learning and Applications.
[2] Nasser Kehtarnavaz,et al. Fusion of depth, skeleton, and inertial data for human action recognition , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[3] Nasser Kehtarnavaz,et al. Real-time human action recognition based on depth motion maps , 2016, Journal of Real-Time Image Processing.
[4] Paul J. M. Havinga,et al. Activity Recognition Using Inertial Sensing for Healthcare, Wellbeing and Sports Applications: A Survey , 2010, ARCS Workshops.
[5] Limin Wang,et al. Multi-view Super Vector for Action Recognition , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[6] Mohan S. Kankanhalli,et al. Multimodal fusion for multimedia analysis: a survey , 2010, Multimedia Systems.
[7] Yuqing Chen,et al. A Deep Learning Approach to Human Activity Recognition Based on Single Accelerometer , 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.
[8] Wei Liu,et al. Gated Fusion Network for Single Image Dehazing , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[9] Max Q.-H. Meng,et al. A Gait Recognition Method for Human Following in Service Robots , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.
[10] Xinyu Li,et al. A Survey of Deep Learning-Based Human Activity Recognition in Radar , 2019, Remote. Sens..
[11] Nasser Kehtarnavaz,et al. Action Detection and Recognition in Continuous Action Streams by Deep Learning-Based Sensing Fusion , 2018, IEEE Sensors Journal.
[12] Nasser Kehtarnavaz,et al. A Real-Time Human Action Recognition System Using Depth and Inertial Sensor Fusion , 2016, IEEE Sensors Journal.
[13] James W. Davis,et al. The Recognition of Human Movement Using Temporal Templates , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[14] Nasser Kehtarnavaz,et al. Fusion of Video and Inertial Sensing for Deep Learning–Based Human Action Recognition , 2019, Sensors.
[15] Patrick Olivier,et al. Feature Learning for Activity Recognition in Ubiquitous Computing , 2011, IJCAI.
[16] Naimul Mefraz Khan,et al. Multidomain Multimodal Fusion for Human Action Recognition Using Inertial Sensors , 2019, 2019 IEEE Fifth International Conference on Multimedia Big Data (BigMM).
[17] Levi J. Hargrove,et al. A Novel Method for Bilateral Gait Segmentation Using a Single Thigh-Mounted Depth Sensor and IMU , 2018, 2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob).
[18] Lei Wang,et al. A Comparative Review of Recent Kinect-Based Action Recognition Algorithms , 2019, IEEE Transactions on Image Processing.
[19] Ling Bao,et al. Activity Recognition from User-Annotated Acceleration Data , 2004, Pervasive.
[20] Nasser Kehtarnavaz,et al. Real-Time Continuous Detection and Recognition of Subject-Specific Smart TV Gestures via Fusion of Depth and Inertial Sensing , 2018, IEEE Access.
[21] Youngbae Hwang,et al. Robust Deep Multi-modal Learning Based on Gated Information Fusion Network , 2018, ACCV.
[22] Nasser Kehtarnavaz,et al. A Convolutional Neural Network-Based Sensor Fusion System for Monitoring Transition Movements in Healthcare Applications , 2018, 2018 IEEE 14th International Conference on Control and Automation (ICCA).
[23] Xiaodong Yang,et al. Recognizing actions using depth motion maps-based histograms of oriented gradients , 2012, ACM Multimedia.
[24] Jake K. Aggarwal,et al. Human activity recognition from 3D data: A review , 2014, Pattern Recognit. Lett..
[25] Allen Y. Yang,et al. Distributed recognition of human actions using wearable motion sensor networks , 2009, J. Ambient Intell. Smart Environ..
[26] Yuning Jiang,et al. DeepDualMapper: A Gated Fusion Network for Automatic Map Extraction using Aerial Images and Trajectories , 2020, AAAI.
[27] Xiaohui Peng,et al. Deep Learning for Sensor-based Activity Recognition: A Survey , 2017, Pattern Recognit. Lett..
[28] Andrew W. Fitzgibbon,et al. Real-time human pose recognition in parts from single depth images , 2011, CVPR 2011.
[29] Fatos T. Yarman-Vural,et al. Automatic Image Annotation by Ensemble of Visual Descriptors , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[30] Raffaele Limosani,et al. Enhancing Activity Recognition of Self-Localized Robot Through Depth Camera and Wearable Sensors , 2018, IEEE Sensors Journal.
[31] Raja Bala,et al. Deep Temporal Multimodal Fusion for Medical Procedure Monitoring Using Wearable Sensors , 2018, IEEE Transactions on Multimedia.
[32] Nasser Kehtarnavaz,et al. Data Augmentation in Deep Learning-Based Fusion of Depth and Inertial Sensing for Action Recognition , 2019, IEEE Sensors Letters.
[33] Sergio Escalera,et al. RGB-D-based Human Motion Recognition with Deep Learning: A Survey , 2017, Comput. Vis. Image Underst..
[34] Bhabatosh Chanda,et al. Space-Time Facet Model for Human Activity Classification , 2014, IEEE Transactions on Multimedia.
[35] Nasser Kehtarnavaz,et al. Simultaneous Utilization of Inertial and Video Sensing for Action Detection and Recognition in Continuous Action Streams , 2020, IEEE Sensors Journal.
[36] Graham W. Taylor,et al. Deep Multimodal Learning: A Survey on Recent Advances and Trends , 2017, IEEE Signal Processing Magazine.
[37] Lihong Zheng,et al. A Survey on Human Action Recognition Using Depth Sensors , 2015, 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA).
[38] James J. Little,et al. Real-Time Human Motion Capture with Multiple Depth Cameras , 2016, 2016 13th Conference on Computer and Robot Vision (CRV).
[39] Nasser Kehtarnavaz,et al. UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor , 2015, 2015 IEEE International Conference on Image Processing (ICIP).
[40] Katsuyuki Sakuma,et al. Wearable Nail Deformation Sensing for Behavioral and Biomechanical Monitoring and Human-Computer Interaction , 2018, Scientific Reports.
[41] Yujie Wang,et al. WiAct: A Passive WiFi-Based Human Activity Recognition System , 2020, IEEE Sensors Journal.
[42] Wei-Yun Yau,et al. Human Action Recognition With Video Data: Research and Evaluation Challenges , 2014, IEEE Transactions on Human-Machine Systems.
[43] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[44] Ruzena Bajcsy,et al. Berkeley MHAD: A comprehensive Multimodal Human Action Database , 2013, 2013 IEEE Workshop on Applications of Computer Vision (WACV).
[45] Zeeshan Ahmad,et al. Human Action Recognition Using Deep Multilevel Multimodal ( ${M}^{2}$ ) Fusion of Depth and Inertial Sensors , 2019, IEEE Sensors Journal.
[46] Kandasamy Illanko,et al. Human Action Recognition Using Convolutional Neural Network and Depth Sensor Data , 2019, Proceedings of the 2019 International Conference on Information Technology and Computer Communications - ITCC 2019.
[47] Zhaozheng Yin,et al. Human Activity Recognition Using Wearable Sensors by Deep Convolutional Neural Networks , 2015, ACM Multimedia.
[48] Fatma Kalaoglu,et al. Human Action Recognition Using Deep Learning Methods on Limited Sensory Data , 2020, IEEE Sensors Journal.
[49] Naimul Mefraz Khan,et al. Towards Improved Human Action Recognition Using Convolutional Neural Networks and Multimodal Fusion of Depth and Inertial Sensor Data , 2018, 2018 IEEE International Symposium on Multimedia (ISM).
[50] Saeed Amirgholipour,et al. Effect of Locations of Using High Boost Filtering on the Watermark Recovery in Spatial Domain Watermarking , 2014 .
[51] Nasser Kehtarnavaz,et al. A survey of depth and inertial sensor fusion for human action recognition , 2015, Multimedia Tools and Applications.
[52] Wanqing Li,et al. Action recognition based on a bag of 3D points , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.
[53] Nathan Intrator,et al. A Real-Time Kinect Signature-Based Patient Home Monitoring System , 2016, Sensors.
[54] Andreas Krause,et al. Unsupervised, dynamic identification of physiological and activity context in wearable computing , 2003, Seventh IEEE International Symposium on Wearable Computers, 2003. Proceedings..
[55] Nasser Kehtarnavaz,et al. Fusion of Inertial and Depth Sensor Data for Robust Hand Gesture Recognition , 2014, IEEE Sensors Journal.
[56] Jinwen Ma,et al. DMMs-Based Multiple Features Fusion for Human Action Recognition , 2015, Int. J. Multim. Data Eng. Manag..
[57] Nasser Kehtarnavaz,et al. Improving Human Action Recognition Using Fusion of Depth Camera and Inertial Sensors , 2015, IEEE Transactions on Human-Machine Systems.
[58] Tan-Hsu Tan,et al. Multi-Resident Activity Recognition in a Smart Home Using RGB Activity Image and DCNN , 2018, IEEE Sensors Journal.
[59] Esther Rodríguez-Villegas,et al. Breathing Detection: Towards a Miniaturized, Wearable, Battery-Operated Monitoring System , 2008, IEEE Transactions on Biomedical Engineering.
[60] Mohamed Atri,et al. An efficient end-to-end deep learning architecture for activity classification , 2018, Analog Integrated Circuits and Signal Processing.
[61] Gaddi Blumrosen,et al. Noncontact Wideband Sonar for Human Activity Detection and Classification , 2014, IEEE Sensors Journal.
[62] Zeeshan Ahmad,et al. Human Action Recognition Using Deep Multilevel Multimodal (M2) Fusion of Depth and Inertial Sensors. , 2019 .
[63] Aun Irtaza,et al. Robust Human Activity Recognition Using Multimodal Feature-Level Fusion , 2019, IEEE Access.
[64] Nasser Kehtarnavaz,et al. C-MHAD: Continuous Multimodal Human Action Dataset of Simultaneous Video and Inertial Sensing , 2020, Sensors.
[65] Wen Gao,et al. Event Tactic Analysis Based on Broadcast Sports Video , 2009, IEEE Trans. Multim..
[66] Alfian Abdul Halin,et al. Feature selection via dimensionality reduction for object class recognition , 2011, 2011 2nd International Conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering.
[67] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .