Structured Time Series Analysis for Human Action Segmentation and Recognition

Keywords

Artificial intelligence, Dynamic time warping, Computer science, Segmentation, Pattern recognition (psychology)

References

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• Bayesian Online Changepoint DetectionRyan P. Adams, David Mackay — 2007
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• Joint segmentation and classification of human actions in videoMinh Hoai, Zhenzhong Lan, Fernando De la Torre — 2011
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• Unsupervised Learning of Human Action Categories Using Spatial-Temporal WordsJuan Carlos Niebles, Hesheng Wang, Hongcheng Wang — 2008
• 3D People Tracking with Gaussian Process Dynamical ModelsRaquel Urtasun, David J. Fleet, Pascal Fua — 2006
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• Dynamic Manifold Warping for view invariant action recognitionDian Gong, Gérard Medioni — 2011
• Canonical Correlation Analysis of Video Volume Tensors for Action Categorization and DetectionTae‐Kyun Kim, Roberto Cipolla — 2009
• Detecting unusual activity in videoHua Zhong, Jianbo Shi, Mirkó Visontai — 2004

Cited by

• Human action recognition via multi-task learning base on spatial-temporal featureWenzhong Guo, Guolong Chen — 2015
• Hierarchical recurrent neural network for skeleton based action recognitionY. Du, Wei Wang, Liang Wang — 2015
• Accurate 3D action recognition using learning on the Grassmann manifoldRim Slama, Hazem Wannous, Mohamed Daoudi — 2015
• 3D skeleton-based human action classification: A surveyLiliana Lo Presti, Marco La Cascia — 2016
• Efficient Unsupervised Temporal Segmentation of Motion DataBjörn Krüger, Anna Vögele, Tobias Willig — 2015
• Space-Time Representation of People Based on 3D Skeletal Data: A ReviewFei Han, Brian Reily, William Hoff — 2016
• Bayesian Non-parametric Inference for Manifold Based MoCap RepresentationFabrizio Natola, Valsamis Ntouskos, Marta Sanzari — 2015
• Unsupervised, efficient and scalable key-frame selection for automatic summarization of surveillance videosGuoliang Lu, Yiqi Zhou, Xueyong Li — 2016
• New localization strategy for mobile robot transportation in life science automation using StarGazer sensor, time series modeling and Kalman filter processingHui Liu, Norbert Stoll, Steffen Junginger — 2015
• Image Segmentation by Student's-t Mixture Models Based on Markov Random Field and Weighted Mean TemplateXu Pan, Hongqing Zhu, Qunyi Xie — 2016
• Generating Local Temporal Poses from Gestures with Aligned Cluster Analysis for Human Action RecognitionMike Edwards, Xianghua Xie — 2015
• Virtual Chime-Bells Experimental System Based on Multi-modal FusionZhifeng Wang, Qingtang Liu, Huang Yao — 2015
• Graph-based representation learning for automatic human motion segmentationMeng Li, Howard Leung — 2016
• Sparse visual signal representations and selected applicationsTzu-Yi Hung — 2015
• Ascertainment-adjusted parameter estimation approach to improve robustness against misspecification of health monitoring methodsPablo Juesas, Emmanuel Ramasso — 2016
• Automatic and Generic Evaluation of Spatial and Temporal Errors in Sport MotionsMarion Morel, Richard Kulpa, Anthony Sorel — 2016
• Sports Motion Recognition Using MCMR Features Based on Interclass Symbolic DistanceYu Wei, Libin Jiao, Shenling Wang — 2016
• Human activity recognition and gymnastics analysis through depth imageryBrian Reily — 2016
• High performance moves recognition and sequence segmentation based on key poses filteringCláudio Márcio de Souza Vicente, Erickson R. Nascimento, Luiz Eduardo C. Emery — 2016
• Skeleton based action recognition with convolutional neural networkYong Du, Yun Fu, Liang Wang — 2015

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