Research on Repetition Counting Method Based on Complex Action Label String
Smart factories have real-time demands for the statistics of productivity to meet the needs of quick reaction capabilities. To solve this problem, a counting method based on our decomposition strategy of actions was proposed for complex actions. Our method needs to decompose complex actions into sev...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/10/6/419 |
| _version_ | 1827659119741370368 |
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| author | Fanghong Yang Gao Wang Deping Li Ning Liu Feiyan Min |
| author_facet | Fanghong Yang Gao Wang Deping Li Ning Liu Feiyan Min |
| author_sort | Fanghong Yang |
| collection | DOAJ |
| description | Smart factories have real-time demands for the statistics of productivity to meet the needs of quick reaction capabilities. To solve this problem, a counting method based on our decomposition strategy of actions was proposed for complex actions. Our method needs to decompose complex actions into several essential actions and define a label string for each complex action according to the sequence of the essential actions. While counting, we firstly employ an online action recognition algorithm to transform video frames into label numbers, which will be stored in a result queue. Then, the label strings are searched for their results in queue. If the search succeeds, a complex action will be considered to have occurred. Meanwhile, the corresponding counter should be updated to accomplish counting. The comparison test results in a video dataset of workers’ repetitive movements in package printing production lines and illustrate that our method has a lower counting errors, MAE (mean absolute error) less than 5% as well as an OBOA (off-by-one accuracy) more than 90%. Moreover, to enhance the adaptability of the action recognition model to deal with the change of action duration, we propose an adaptive parameter module based on the Kalman filter, which improves counting performances to a certain extent. The conclusions are that our method can achieve high counting performance, and the adaptive parameter module can further improve performances. |
| first_indexed | 2024-03-09T23:15:07Z |
| format | Article |
| id | doaj.art-d364e238e85b4f3cbc788b0f98175327 |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-03-09T23:15:07Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-d364e238e85b4f3cbc788b0f981753272023-11-23T17:38:48ZengMDPI AGMachines2075-17022022-05-0110641910.3390/machines10060419Research on Repetition Counting Method Based on Complex Action Label StringFanghong Yang0Gao Wang1Deping Li2Ning Liu3Feiyan Min4Department of Electronic Engineering, College of Information Science and Technology, Jinan University, Guangzhou 510632, ChinaDepartment of Electronic Engineering, College of Information Science and Technology, Jinan University, Guangzhou 510632, ChinaSchool of Intelligent Systems Science and Engineering, Jinan University, Zhuhai 519070, ChinaDepartment of Electronic Engineering, College of Information Science and Technology, Jinan University, Guangzhou 510632, ChinaDepartment of Electronic Engineering, College of Information Science and Technology, Jinan University, Guangzhou 510632, ChinaSmart factories have real-time demands for the statistics of productivity to meet the needs of quick reaction capabilities. To solve this problem, a counting method based on our decomposition strategy of actions was proposed for complex actions. Our method needs to decompose complex actions into several essential actions and define a label string for each complex action according to the sequence of the essential actions. While counting, we firstly employ an online action recognition algorithm to transform video frames into label numbers, which will be stored in a result queue. Then, the label strings are searched for their results in queue. If the search succeeds, a complex action will be considered to have occurred. Meanwhile, the corresponding counter should be updated to accomplish counting. The comparison test results in a video dataset of workers’ repetitive movements in package printing production lines and illustrate that our method has a lower counting errors, MAE (mean absolute error) less than 5% as well as an OBOA (off-by-one accuracy) more than 90%. Moreover, to enhance the adaptability of the action recognition model to deal with the change of action duration, we propose an adaptive parameter module based on the Kalman filter, which improves counting performances to a certain extent. The conclusions are that our method can achieve high counting performance, and the adaptive parameter module can further improve performances.https://www.mdpi.com/2075-1702/10/6/419action countingaction decompositioncomplex action label stringtemplate matchingKalman filtering |
| spellingShingle | Fanghong Yang Gao Wang Deping Li Ning Liu Feiyan Min Research on Repetition Counting Method Based on Complex Action Label String Machines action counting action decomposition complex action label string template matching Kalman filtering |
| title | Research on Repetition Counting Method Based on Complex Action Label String |
| title_full | Research on Repetition Counting Method Based on Complex Action Label String |
| title_fullStr | Research on Repetition Counting Method Based on Complex Action Label String |
| title_full_unstemmed | Research on Repetition Counting Method Based on Complex Action Label String |
| title_short | Research on Repetition Counting Method Based on Complex Action Label String |
| title_sort | research on repetition counting method based on complex action label string |
| topic | action counting action decomposition complex action label string template matching Kalman filtering |
| url | https://www.mdpi.com/2075-1702/10/6/419 |
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