基于多模态数据的行为和手势识别
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作者张亮
出版社西安电子科技大学出版社
ISBN9787560665399
出版时间2022-08
装帧平装
开本其他
定价40元
货号31534045
上书时间2024-05-25
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目录
Chapter 1 Human Action Recognition Using MultMayer Codebooks of Key Poses and Atomic Motions
1.1 Introduction
1.2 Related Work
1.2.1 Feature Representation
1.2.2 Classification Model
1.3 Construction of Multi-layer Codebook
1.3.1 Feature Representation
1.3.2 Feature Sequence Segmentation
1,3.3 Pose-layer Codebook
1.3.4 Motion-layer Codebook
1.3.5 Multi-layer Codebook Construction
1.4 Classification Methods
1.4.1 Naive Bayes Nearest Neighbor
1.4.2 Support Vector Machine
1.4.3 Random Forest
1.5 Experimental Results
1.5.1 Experiments on the CAD-60 dataset
1.5.2 Experiments on the MSRC-12 dataset
1.5.3 Discussion
1.6 Conclusion and Future Work
Acknowledgements
References
Chapter 2 Topology-learnable Graph Convolution for Skeleton-based Action Recognition
2.1 Introduction
2.2 Related Work
2.2.1 Graph Convolutional Network for Action Recognition
2.2.2 Adaptive Graph Convolution
2.3 Topology-learnable Graph Convolution
2.3.1 Graph Convolution
2.3.2 Graph Topology Analysis
2.3.3 Topology-learnable Graph Convolution
2.3.4 Topology-learnable GCNs
2.4 Experiments
2.4.1 Datasets
2.4.2 Ablation Study
2.4.3 Comparison with the State-of-the-art Methods
2.4.4 Discussion
2.5 Conclusion
Acknowledgements
References
Chapter 3 Recurrent Graph Convolutional Networks for Skeleton-based Action Recognition
3.1 Introduction
3.2 Related Work
3.2.1 Graph Convolution for Action Recognition
3.2.2 LSTM on Graphs
3.3 Recurrent Graph Convolutional Network
3.3.1 Graph Convolution
3.3.2 Adaptive Graph Convolution
3.3.3 Recurrent Graph Convolution
3.3.4 Recurrent Graph Convolutional Network
内容摘要
Thisbookprovidesaseriesofgestureandbehaviorrecognitionmethodsbasedonmultimodaldatarepresentation.Thedatamodalitiesincludeimagedataandskeletondata,andthemodelingmethodsincludetraditionalcodebook,topologicalgraph,andLSTMarchitectures.Thetasksincludesinglegesturerecognitionclassification,singleactionrecognitionclassification,continuousgestureclassification,complexbehaviorclassificationofhumaninteractionandothertasksofdifferentcomplexity.Thisbookfocusesonthedataprocessingmethodsofeachmodality,andthemodelingmethodsfordifferenttasks.Wehopethereadercanlearnbasicgestureandactionrecognitionmethodsfromthisbook,anddevelopamodelsystemthatsuitstheirneedsonthisbasis.Thisbookcanbeusedasatextbookforgraduate,postgraduateandPhDstudentsmajoringincomputerscience,automation,etc.Itcanalsobeusedasareferenceforthereaderwhoisinterestedingesturerecognition,humanactioninteraction,sequencedataprocessing,anddeepneuralnetworkdesign,andwhohopestocontributetothefields.
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