Sleep Action Recognition Based on Segmentation Strategy Article Swipe
Xiang Zhou
,
Yue Cui
,
Gang Xu
,
Hongliang Chen
,
Jing Zeng
,
Yutong Li
,
Jiangjian Xiao
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/jimaging9030060
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/jimaging9030060
In order to solve the problem of long video dependence and the difficulty of fine-grained feature extraction in the video behavior recognition of personnel sleeping at a security-monitored scene, this paper proposes a time-series convolution-network-based sleeping behavior recognition algorithm suitable for monitoring data. ResNet50 is selected as the backbone network, and the self-attention coding layer is used to extract rich contextual semantic information; then, a segment-level feature fusion module is constructed to enhance the effective transmission of important information in the segment feature sequence on the network, and the long-term memory network is used to model the entire video in the time dimension to improve behavior detection ability. This paper constructs a data set of sleeping behavior under security monitoring, and the two behaviors contain about 2800 single-person target videos. The experimental results show that the detection accuracy of the network model in this paper is significantly improved on the sleeping post data set, up to 6.69% higher than the benchmark network. Compared with other network models, the performance of the algorithm in this paper has improved to different degrees and has good application value.
Related Topics
Concepts
Computer science
Artificial intelligence
Benchmark (surveying)
Pattern recognition (psychology)
Feature extraction
Feature (linguistics)
Segmentation
Activity recognition
Coding (social sciences)
Set (abstract data type)
Data mining
Linguistics
Geodesy
Statistics
Geography
Mathematics
Programming language
Philosophy
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/jimaging9030060
- https://www.mdpi.com/2313-433X/9/3/60/pdf?version=1678175783
- OA Status
- gold
- Cited By
- 1
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4323361574
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4323361574Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/jimaging9030060Digital Object Identifier
- Title
-
Sleep Action Recognition Based on Segmentation StrategyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-03-07Full publication date if available
- Authors
-
Xiang Zhou, Yue Cui, Gang Xu, Hongliang Chen, Jing Zeng, Yutong Li, Jiangjian XiaoList of authors in order
- Landing page
-
https://doi.org/10.3390/jimaging9030060Publisher landing page
- PDF URL
-
https://www.mdpi.com/2313-433X/9/3/60/pdf?version=1678175783Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2313-433X/9/3/60/pdf?version=1678175783Direct OA link when available
- Concepts
-
Computer science, Artificial intelligence, Benchmark (surveying), Pattern recognition (psychology), Feature extraction, Feature (linguistics), Segmentation, Activity recognition, Coding (social sciences), Set (abstract data type), Data mining, Linguistics, Geodesy, Statistics, Geography, Mathematics, Programming language, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- References (count)
-
31Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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