Deep Learning-Based Action Recognition

• Outros Autores: Lee, Hyo Jong (Editor)
• Formato: Recurso Eletrônico Capítulo de Livro
• Idioma: inglês
• Publicado em: MDPI - Multidisciplinary Digital Publishing Institute 2022
• Assuntos: Technology: general issues; History of engineering & technology; human action recognition; graph convolution; high-order feature; spatio-temporal feature; feature fusion; dynamic gesture recognition; multi-modalities network; class regularization; 3D-CNN; spatiotemporal activations; class-specific features; Dynamic Hand Gesture Recognition; human-computer interaction; hand shape features; pose estimation; stacked hourglass network; deep learning; convolutional receptive field; hand gesture recognition; human-machine interface; artificial intelligence; feedforward neural networks; spatio-temporal image formation; human activity recognition; fusion strategies; transfer learning; activity recognition; data augmentation; multi-person pose estimation; partitioned centerpose network; partition pose representation; continuous hand gesture recognition; gesture spotting; gesture classification; multi-modal features; 3D skeletal; CNN; spatiotemporal feature; embedded system; real-time; action recognition; Long Short-Term Memory; spatio-temporal differential; n/a
• Acesso em linha: DOAB: download the publication; DOAB: description of the publication

The classification of human action or behavior patterns is very important for analyzing situations in the field and maintaining social safety. This book focuses on recent research findings on recognizing human action patterns. Technology for the recognition of human action pattern includes the proce...