Title
A Deep Clustering via Automatic Feature Embedded Learning for Human Activity Recognition
Abstract
Traditional clustering algorithms are widely used for building bag-of-words (BOW) models to aggregate spatio-temporal feature points extracted from a video for human activity recognition problems. Their performances are restricted by the computational complexity which limits the number of feature points being used. In contrast, deep clustering yields good clustering performance without the limit o...
Year
DOI
Venue
2022
10.1109/TCSVT.2021.3057469
IEEE Transactions on Circuits and Systems for Video Technology
Keywords
DocType
Volume
Feature extraction,Clustering algorithms,Clustering methods,Visualization,Activity recognition,Vocabulary,Task analysis
Journal
32
Issue
ISSN
Citations 
1
1051-8215
0
PageRank 
References 
Authors
0.34
13
7
Name
Order
Citations
PageRank
Ting Wang1725120.28
Wing W. Y. Ng252856.12
Jinde Li300.34
Qiuxia Wu41039.25
Shuai Zhang5439.10
Chris D. Nugent61150128.39
Colin Shewell761.92