Multiperson Interactive Activity Recognition Based on Interaction Relation Model
Multiperson activity recognition is a pivotal branch as well as a challenging topic of human action recognition research. This paper adopts a hybrid learning model to the spatio-temporal relationship and occlusion relationship among multiple people. Initially, this paper builds up an active multiper...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2021/5576369 |
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| _version_ | 1832546044840247296 |
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| author | Hongbin Tu Renyu Xu Rui Chi Yuanyuan Peng |
| author_facet | Hongbin Tu Renyu Xu Rui Chi Yuanyuan Peng |
| author_sort | Hongbin Tu |
| collection | DOAJ |
| description | Multiperson activity recognition is a pivotal branch as well as a challenging topic of human action recognition research. This paper adopts a hybrid learning model to the spatio-temporal relationship and occlusion relationship among multiple people. Initially, this paper builds up an active multiperson interaction relationship estimation framework model to capture interpersonal spatio-temporal relation. This model incorporates the interaction relationship estimation framework with the multiperson relationship network. On this ground, it automatically learns from the human-computer interaction dataset in an end-to-end manner and performs reasoning with standard matrix operations. Secondly, this paper proposed an adaptive occlusion state behavior recognition method derived from the semantic knowledge model to ravel out the concern of occlusion and self-occlusion in human action recognition. Then, Petri Nets are used to recognize multiperson interactive actions. This model has been through extensive experiments on the TV interaction dataset, Vlog dataset, AVA dataset, and MLB-YouTube dataset, experimental results have proved that the recognition performance of this model is superior than the other available models. This paper prospects and summarizes the estimation framework of the interaction relationship and occlusion semantic-knowledge relationship. Experimental results suggest that the proposed method in the paper could capture the discriminative relation information for multiperson interactive activity recognition, which further validates the efficiency of the hybrid learning model. |
| format | Article |
| id | doaj-art-27a7ffe008a64f44b9df0fe95e9faefb |
| institution | Kabale University |
| issn | 2314-4629 2314-4785 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-27a7ffe008a64f44b9df0fe95e9faefb2025-02-03T07:24:00ZengWileyJournal of Mathematics2314-46292314-47852021-01-01202110.1155/2021/55763695576369Multiperson Interactive Activity Recognition Based on Interaction Relation ModelHongbin Tu0Renyu Xu1Rui Chi2Yuanyuan Peng3School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, ChinaSchool of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, ChinaSchool of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, ChinaSchool of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, ChinaMultiperson activity recognition is a pivotal branch as well as a challenging topic of human action recognition research. This paper adopts a hybrid learning model to the spatio-temporal relationship and occlusion relationship among multiple people. Initially, this paper builds up an active multiperson interaction relationship estimation framework model to capture interpersonal spatio-temporal relation. This model incorporates the interaction relationship estimation framework with the multiperson relationship network. On this ground, it automatically learns from the human-computer interaction dataset in an end-to-end manner and performs reasoning with standard matrix operations. Secondly, this paper proposed an adaptive occlusion state behavior recognition method derived from the semantic knowledge model to ravel out the concern of occlusion and self-occlusion in human action recognition. Then, Petri Nets are used to recognize multiperson interactive actions. This model has been through extensive experiments on the TV interaction dataset, Vlog dataset, AVA dataset, and MLB-YouTube dataset, experimental results have proved that the recognition performance of this model is superior than the other available models. This paper prospects and summarizes the estimation framework of the interaction relationship and occlusion semantic-knowledge relationship. Experimental results suggest that the proposed method in the paper could capture the discriminative relation information for multiperson interactive activity recognition, which further validates the efficiency of the hybrid learning model.http://dx.doi.org/10.1155/2021/5576369 |
| spellingShingle | Hongbin Tu Renyu Xu Rui Chi Yuanyuan Peng Multiperson Interactive Activity Recognition Based on Interaction Relation Model Journal of Mathematics |
| title | Multiperson Interactive Activity Recognition Based on Interaction Relation Model |
| title_full | Multiperson Interactive Activity Recognition Based on Interaction Relation Model |
| title_fullStr | Multiperson Interactive Activity Recognition Based on Interaction Relation Model |
| title_full_unstemmed | Multiperson Interactive Activity Recognition Based on Interaction Relation Model |
| title_short | Multiperson Interactive Activity Recognition Based on Interaction Relation Model |
| title_sort | multiperson interactive activity recognition based on interaction relation model |
| url | http://dx.doi.org/10.1155/2021/5576369 |
| work_keys_str_mv | AT hongbintu multipersoninteractiveactivityrecognitionbasedoninteractionrelationmodel AT renyuxu multipersoninteractiveactivityrecognitionbasedoninteractionrelationmodel AT ruichi multipersoninteractiveactivityrecognitionbasedoninteractionrelationmodel AT yuanyuanpeng multipersoninteractiveactivityrecognitionbasedoninteractionrelationmodel |