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Full-Text Articles in Physical Sciences and Mathematics
Human Motion Simulation And Action Corpus, Gang Zheng, Wanqing Li, Philip Ogunbona, Liju Dong, Igor Kharitonenko
Human Motion Simulation And Action Corpus, Gang Zheng, Wanqing Li, Philip Ogunbona, Liju Dong, Igor Kharitonenko
Associate Professor Wanqing Li
Acquisition of large scale good quality training samples is becoming a major issue in machine learning based human motion analysis. This paper presents a method to simulate continuous gross human body motion with the intention to establish a human motion corpus for learning and recognition. The simulation is achieved by a temporal-spatialtemporal decomposition of human motion into actions, joint actions and actionlets based on the human kinematic model. The actionlet models the primitive moving phase of a joint and represents the muscle movement governed by kinesiological principles. Joint actions and body actions are constructed from actionlets through constrained concatenation and …
Research Of Unsupervised Posture Modeling And Action Recognition Based On Spatial-Temporal Interesting Points, Chuan-Xu Wang, Yun Liu, Wanqing Li
Research Of Unsupervised Posture Modeling And Action Recognition Based On Spatial-Temporal Interesting Points, Chuan-Xu Wang, Yun Liu, Wanqing Li
Associate Professor Wanqing Li
Posture modeling is critical for action description and recognition,a posture modeling and action recognition method is proposed in this paper.Spatial Temporal Interesting Points (STIPs) are extracted from learning samples,in fact,one posture consists of a set of STIPs;a unsupervised clustering method is adopted to classify salient postures from these posture samples,then a GMM model is established for each clustering result;transitional probability among salient postures are calculated,and a Visible state Markov Model(VMM) is learnt to describe various actions.Bi-gram method is put forward for action recognition,Extensive experiments are conducted and the results prove its robustness and validity.
Human Motion Simulation And Action Corpus, Gang Zheng, Wanqing Li, Philip Ogunbona, Liju Dong, Igor Kharitonenko
Human Motion Simulation And Action Corpus, Gang Zheng, Wanqing Li, Philip Ogunbona, Liju Dong, Igor Kharitonenko
Dr Igor Kharitonenko
Acquisition of large scale good quality training samples is becoming a major issue in machine learning based human motion analysis. This paper presents a method to simulate continuous gross human body motion with the intention to establish a human motion corpus for learning and recognition. The simulation is achieved by a temporal-spatialtemporal decomposition of human motion into actions, joint actions and actionlets based on the human kinematic model. The actionlet models the primitive moving phase of a joint and represents the muscle movement governed by kinesiological principles. Joint actions and body actions are constructed from actionlets through constrained concatenation and …
Human Motion Simulation And Action Corpus, Gang Zheng, Wanqing Li, Philip Ogunbona, Liju Dong, Igor Kharitonenko
Human Motion Simulation And Action Corpus, Gang Zheng, Wanqing Li, Philip Ogunbona, Liju Dong, Igor Kharitonenko
Professor Philip Ogunbona
Acquisition of large scale good quality training samples is becoming a major issue in machine learning based human motion analysis. This paper presents a method to simulate continuous gross human body motion with the intention to establish a human motion corpus for learning and recognition. The simulation is achieved by a temporal-spatialtemporal decomposition of human motion into actions, joint actions and actionlets based on the human kinematic model. The actionlet models the primitive moving phase of a joint and represents the muscle movement governed by kinesiological principles. Joint actions and body actions are constructed from actionlets through constrained concatenation and …