Automatic Recognition of Human Interaction via Hybrid Descriptors and Maximum Entropy Markov Model Using Depth Sensors
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Kibum Kim | Ahmad Jalal | Nida Khalid | A. Jalal | Kibum Kim | Nida Khalid
[1] Xiaohui Xie,et al. Co-Occurrence Feature Learning for Skeleton Based Action Recognition Using Regularized Deep LSTM Networks , 2016, AAAI.
[2] Ahmad Jalal,et al. Facial Expression Recognition in Image Sequences Using 1D Transform and Gabor Wavelet Transform , 2018, 2018 International Conference on Applied and Engineering Mathematics (ICAEM).
[3] Yannick Benezeth,et al. Human Interaction Recognition Based on the Co-occurrence of Visual Words , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops.
[4] Hong Cheng,et al. Interactive body part contrast mining for human interaction recognition , 2014, 2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW).
[5] C. N. Scanaill,et al. Body-Worn, Ambient, and Consumer Sensing for Health Applications , 2013 .
[6] Hongnian Yu,et al. Elderly activities recognition and classification for applications in assisted living , 2013, Expert Syst. Appl..
[7] Y.-K. Lee,et al. Human Activity Recognition via an Accelerometer-Enabled-Smartphone Using Kernel Discriminant Analysis , 2010, 2010 5th International Conference on Future Information Technology.
[8] Atsuo Yoshitaka,et al. Human Interaction Recognition Using Hierarchical Invariant Features , 2015, Int. J. Semantic Comput..
[9] Chao Lan,et al. Markov Model , 2010, Encyclopedia of Machine Learning.
[10] W Singhose. A Comparison of Dual-Kinect and Vicon Tracking of Human Motion for Use in Robotic Motion Programming , 2017, ICRA 2017.
[11] Aun Irtaza,et al. Robust Human Activity Recognition Using Multimodal Feature-Level Fusion , 2019, IEEE Access.
[12] Mooi Choo Chuah,et al. Category-Blind Human Action Recognition: A Practical Recognition System , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[13] Negar Golestani,et al. Human activity recognition using magnetic induction-based motion signals and deep recurrent neural networks , 2020, Nature Communications.
[14] Ahmad Jalal,et al. Salient Segmentation based Object Detection and Recognition using Hybrid Genetic Transform , 2019, 2019 International Conference on Applied and Engineering Mathematics (ICAEM).
[15] Paolo Dario,et al. Two-person activity recognition using skeleton data , 2018, IET Comput. Vis..
[16] Daniel F. Keefe,et al. Poster: A Real-Time Physical Therapy Visualization Strategy to Improve Unsupervised Patient Rehabilitation , 2009 .
[17] Mohamed R. Amer,et al. Sum Product Networks for Activity Recognition , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[18] Unsang Park,et al. Compositional interaction descriptor for human interaction recognition , 2017, Neurocomputing.
[19] Dimitris Samaras,et al. Two-person interaction detection using body-pose features and multiple instance learning , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.
[20] Manouchehr Shokri,et al. A Review on the Artificial Neural Network Approach to Analysis and Prediction of Seismic Damage in Infrastructure , 2019, International Journal of Hydromechatronics.
[21] Duoqian Miao,et al. Influence of kernel clustering on an RBFN , 2019, CAAI Trans. Intell. Technol..
[22] Wei Liang,et al. Recognising human interaction from videos by a discriminative model , 2014, IET Comput. Vis..
[23] Travis Wiens,et al. Engine Speed Reduction for Hydraulic Machinery Using Predictive Algorithms , 2019, International Journal of Hydromechatronics.
[24] Qing Zhang,et al. A Survey on Human Motion Analysis from Depth Data , 2013, Time-of-Flight and Depth Imaging.
[25] Zhaozheng Yin,et al. Human Activity Recognition Using Wearable Sensors by Deep Convolutional Neural Networks , 2015, ACM Multimedia.
[26] Farooq Ahmad,et al. Recognizing Human Activities From Video Using Weakly Supervised Contextual Features , 2019, IEEE Access.
[27] Hala H. Zayed,et al. Human Activity Recognition for Surveillance Applications , 2015, ICIT 2015.
[28] Thuong Le-Tien,et al. PAM-based flexible generative topic model for 3D interactive activity recognition , 2015, 2015 International Conference on Advanced Technologies for Communications (ATC).
[29] Amir Nadeem,et al. Human Actions Tracking and Recognition Based on Body Parts Detection via Artificial Neural Network , 2020, 2020 3rd International Conference on Advancements in Computational Sciences (ICACS).
[30] Shih-Ching Chen,et al. Digitized Hand Skateboard Based on IR-Camera for Upper Limb Rehabilitation , 2016, Journal of Medical Systems.
[31] Marcin Grzegorzek,et al. A generic codebook based approach for gait recognition , 2019, Multimedia Tools and Applications.
[32] Ahmad Jalal,et al. Wearable Sensors for Activity Analysis using SMO-based Random Forest over Smart home and Sports Datasets , 2020, 2020 3rd International Conference on Advancements in Computational Sciences (ICACS).
[33] Daijin Kim,et al. Robust human activity recognition from depth video using spatiotemporal multi-fused features , 2017, Pattern Recognit..
[34] Behzad Moshiri,et al. Trunk Motion System (TMS) Using Printed Body Worn Sensor (BWS) via Data Fusion Approach , 2017, Sensors.
[35] Md. Zia Uddin,et al. A Depth Camera-based Human Activity Recognition via Deep Learning Recurrent Neural Network for Health and Social Care Services , 2016, CENTERIS/ProjMAN/HCist.
[36] Mohammad Saraee,et al. A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments , 2016, Neural Computing and Applications.
[37] Lintai Wu,et al. Three-stage network for age estimation , 2019, CAAI Trans. Intell. Technol..
[38] Ahmad Jalal,et al. Robust Spatio-Temporal Features for Human Interaction Recognition Via Artificial Neural Network , 2018, 2018 International Conference on Frontiers of Information Technology (FIT).
[39] Daijin Kim,et al. A Depth Video Sensor-Based Life-Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments , 2014, Sensors.
[40] Xiaofei Xu,et al. Activity Recognition Method for Home-Based Elderly Care Service Based on Random Forest and Activity Similarity , 2019, IEEE Access.
[41] Li Pan,et al. A Cross-Entropy-Based Admission Control Optimization Approach for Heterogeneous Virtual Machine Placement in Public Clouds , 2016, Entropy.
[42] Bingxian Lin,et al. Detecting Toe-Off Events Utilizing a Vision-Based Method , 2019, Entropy.
[43] Amir Nadeem,et al. Human Body Parts Estimation and Detection for Physical Sports Movements , 2019, 2019 2nd International Conference on Communication, Computing and Digital systems (C-CODE).
[44] Muhammad Sher,et al. Automated multi-feature human interaction recognition in complex environment , 2018, Comput. Ind..
[45] Ahmad Jalal,et al. Wearable Sensor-Based Human Behavior Understanding and Recognition in Daily Life for Smart Environments , 2018, 2018 International Conference on Frontiers of Information Technology (FIT).
[46] Mohsen Rashki,et al. Refined first-order reliability method using cross-entropy optimization method , 2019, Engineering with Computers.
[47] Maria Mahmood,et al. Students’ behavior mining in e-learning environment using cognitive processes with information technologies , 2019, Education and Information Technologies.
[48] Jürgen Weber,et al. Analytical analysis of single-stage pressure relief valves , 2019, International Journal of Hydromechatronics.
[49] Joseph A. Paradiso,et al. A Wide-Range, Wireless Wearable Inertial Motion Sensing System for Capturing Fast Athletic Biomechanics in Overhead Pitching , 2019, Sensors.
[50] Mohand Saïd Allili,et al. Group-of-features relevance in multinomial kernel logistic regression and application to human interaction recognition , 2020, Expert Syst. Appl..
[51] Tae-Seong Kim,et al. Depth video-based human activity recognition system using translation and scaling invariant features for life logging at smart home , 2012, IEEE Transactions on Consumer Electronics.
[52] Kibum Kim,et al. A Novel Statistical Method for Scene Classification Based on Multi-Object Categorization and Logistic Regression , 2020, Sensors.
[53] Marcin Grzegorzek,et al. Marker-Based Movement Analysis of Human Body Parts in Therapeutic Procedure , 2020, Sensors.
[54] Maria Mahmood,et al. WHITE STAG model: wise human interaction tracking and estimation (WHITE) using spatio-temporal and angular-geometric (STAG) descriptors , 2019, Multimedia Tools and Applications.
[55] Daijin Kim,et al. Shape and Motion Features Approach for Activity Tracking and Recognition from Kinect Video Camera , 2015, 2015 IEEE 29th International Conference on Advanced Information Networking and Applications Workshops.
[56] Meng Li,et al. Multi-view depth-based pairwise feature learning for person-person interaction recognition , 2019, Multimedia Tools and Applications.
[57] Maria Mahmood,et al. Multi-features descriptors for Human Activity Tracking and Recognition in Indoor-Outdoor Environments , 2019, 2019 16th International Bhurban Conference on Applied Sciences and Technology (IBCAST).
[58] Haibo Hu,et al. Wearable Sensor-Based Human Activity Recognition Method with Multi-Features Extracted from Hilbert-Huang Transform , 2016, Sensors.
[59] Mehdi Vakilian,et al. Partial Discharges Pattern Recognition of Transformer Defect Model by LBP & HOG Features , 2019, IEEE Transactions on Power Delivery.
[60] Unsang Park,et al. Group Activity Recognition with Group Interaction Zone Based on Relative Distance Between Human Objects , 2015, Int. J. Pattern Recognit. Artif. Intell..
[61] Wenbing Zhao,et al. Rule based realtime motion assessment for rehabilitation exercises , 2014, 2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE).
[62] Jeffrey M. Hausdorff,et al. Validation of a Method for Real Time Foot Position and Orientation Tracking With Microsoft Kinect Technology for Use in Virtual Reality and Treadmill Based Gait Training Programs , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[63] Ahmad Jalal,et al. Wearable Inertial Sensors for Daily Activity Analysis Based on Adam Optimization and the Maximum Entropy Markov Model , 2020, Entropy.
[64] Bob R. Schadenberg. Predictability in Human-Robot Interactions for Autistic Children , 2019, 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI).
[65] Muhammad Younus Javed,et al. A framework of human detection and action recognition based on uniform segmentation and combination of Euclidean distance and joint entropy-based features selection , 2017, EURASIP J. Image Video Process..
[66] Jake K. Aggarwal,et al. Spatio-temporal relationship match: Video structure comparison for recognition of complex human activities , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[67] Edward D. Lemaire,et al. Feature Selection for Wearable Smartphone-Based Human Activity Recognition with Able bodied, Elderly, and Stroke Patients , 2015, PloS one.
[68] Huaijun Wang,et al. Segmentation and Recognition of Basic and Transitional Activities for Continuous Physical Human Activity , 2019, IEEE Access.
[69] Nicola Bellotto,et al. Social activity recognition based on probabilistic merging of skeleton features with proximity priors from RGB-D data , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[70] Zhaojie Ju,et al. A New Framework of Human Interaction Recognition Based on Multiple Stage Probability Fusion , 2017 .
[71] Gernot A. Fink,et al. Human Activity Recognition for Production and Logistics - A Systematic Literature Review , 2019, Inf..
[72] Serhan Cosar,et al. Automatic detection of human interactions from RGB-D data for social activity classification , 2017, 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).
[73] Wei Zhao,et al. A motifs-based Maximum Entropy Markov Model for realtime reliability prediction in System of Systems , 2019, J. Syst. Softw..
[74] Tao Wang,et al. PGNet: Pipeline Guidance for Human Key-Point Detection , 2020, Entropy.
[75] Jake K. Aggarwal,et al. Human activity recognition from 3D data: A review , 2014, Pattern Recognit. Lett..
[76] Seba Susan,et al. New shape descriptor in the context of edge continuity , 2019, CAAI Trans. Intell. Technol..
[77] Ahmad Jalal,et al. Sensors Technologies for Human Activity Analysis Based on SVM Optimized by PSO Algorithm , 2019, 2019 International Conference on Applied and Engineering Mathematics (ICAEM).
[78] Nasser Kehtarnavaz,et al. A survey of depth and inertial sensor fusion for human action recognition , 2015, Multimedia Tools and Applications.
[79] Hong Cheng,et al. Learning contrastive feature distribution model for interaction recognition , 2015, J. Vis. Commun. Image Represent..
[80] Kibum Kim,et al. An Accurate Facial Expression Detector using Multi-Landmarks Selection and Local Transform Features , 2020, 2020 3rd International Conference on Advancements in Computational Sciences (ICACS).
[81] Kibum Kim,et al. RGB-D Images for Object Segmentation, Localization and Recognition in Indoor Scenes using Feature Descriptor and Hough Voting , 2020, 2020 17th International Bhurban Conference on Applied Sciences and Technology (IBCAST).
[82] Ahmad Lotfi,et al. Exploring Entropy Measurements to Identify Multi-Occupancy in Activities of Daily Living , 2019, Entropy.
[83] Adel M. Alimi,et al. Fuzzy Logic Based Human Activity Recognition in Video Surveillance Applications , 2015, AECIA.
[84] Daijin Kim,et al. Human Depth Sensors-Based Activity Recognition Using Spatiotemporal Features and Hidden Markov Model for Smart Environments , 2016, J. Comput. Networks Commun..
[85] Omer Faruk Ince,et al. Human activity recognition with analysis of angles between skeletal joints using a RGB‐depth sensor , 2019, ETRI Journal.
[86] S. Chitrakala,et al. Recognition of human-human interaction using CWDTW , 2016, 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT).
[87] Ahmad Jalal,et al. Region and Decision Tree-Based Segmentations for Multi-Objects Detection and Classification in Outdoor Scenes , 2019, 2019 International Conference on Frontiers of Information Technology (FIT).
[88] Shuang Wang,et al. A Review on Human Activity Recognition Using Vision-Based Method , 2017, Journal of healthcare engineering.
[89] Daijin Kim,et al. Depth silhouettes context: A new robust feature for human tracking and activity recognition based on embedded HMMs , 2015, 2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI).
[90] Majid Ali Khan Quaid,et al. Wearable sensors based human behavioral pattern recognition using statistical features and reweighted genetic algorithm , 2019, Multimedia Tools and Applications.
[91] Daniel W. Bliss,et al. Comparing Gaussian Mixture Model and Hidden Markov Model to Classify Unique Physical Activities from Accelerometer Sensor Data , 2016, 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA).
[92] Ahmad Jalal,et al. A Triaxial Acceleration-based Human Motion Detection for Ambient Smart Home System , 2019, 2019 16th International Bhurban Conference on Applied Sciences and Technology (IBCAST).