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Handcrafted localized phase features for human action recognition

  • Published:2022-07 Issue: Volume:123 Page:104465
  • ISSN:0262-8856
  • Container-title:Image and Vision Computing
  • language:en
  • Short-container-title:Image and Vision Computing

Author:

Hejazi Seyed Mostafa,Abhayaratne Charith

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing

Reference66 articles.

1. A survey on visual surveillance of object motion and behaviors;Hu;IEEE Trans. Syst. Man Cybern. Part C Appl. Rev.,2004

2. A review of human activity recognition methods;Vrigkas;Front. Robot. AI,2015

3. Motion-based recognition a survey;Cédras;Image Vis. Comput.,1995

4. Video based technology for ambient assisted living: a review of the literature;Cardinaux;J. Amb. Intell. Smart Environ.,2011

5. Cross-domain human action recognition;Bian;IEEE Trans. Syst. Man Cybern. Part B (Cybern.),2012

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1. H2GCN: A hybrid hypergraph convolution network for skeleton-based action recognition;Journal of King Saud University - Computer and Information Sciences;2024-06

2. Residual deep gated recurrent unit-based attention framework for human activity recognition by exploiting dilated features;The Visual Computer;2024-02-06

3. Human Action Recognition using Deep Learning Technique;2023 Global Conference on Information Technologies and Communications (GCITC);2023-12-01

4. A Vision-Based Method for Human Activity Recognition Using Local Binary Pattern;2023 13th International Conference on Computer and Knowledge Engineering (ICCKE);2023-11-01

5. ConViViT - A Deep Neural Network Combining Convolutions and Factorized Self-Attention for Human Activity Recognition;2023 IEEE 25th International Workshop on Multimedia Signal Processing (MMSP);2023-09-27
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