Intelligent Video Analytics for Human Action Recognition: The State of Knowledge

被引：2

作者：

Kulbacki, Marek ^{[1
,2
]}

Segen, Jakub ^{[1
,2
]}

Chaczko, Zenon ^{[2
,3
]}

Rozenblit, Jerzy W. ^{[4
]}

Kulbacki, Michal ^{[2
]}

Klempous, Ryszard ^{[5
]}

Wojciechowski, Konrad ^{[1
]}

机构：

[1] Polish Japanese Acad Informat Technol, PL-02008 Warsaw, Poland

[2] DIVE IN AI, PL-53307 Wroclaw, Poland

[3] Univ Technol Sydney, Sch Elect & Data Engn, Ultimo 2007, Australia

[4] Univ Arizona, Dept Elect & Comp Engn, Tucson, AZ 85721 USA

[5] Wroclaw Univ Sci & Technol, PL-50370 Wroclaw, Poland

来源：

SENSORS | 2023年 / 23卷 / 09期

关键词：

intelligent video analytics; edge AI; visual transformers; human activity recognition; video surveillance; pose-based HAR; tracking-based HAR; spatio-temporal-based HAR; deep learning-based HAR; HUMAN POSE ESTIMATION; VISUAL TRACKING; BEHAVIOR ANALYSIS; HUMAN MOVEMENT; MOTION; SURVEILLANCE; ROBUST; MODELS; CLASSIFICATION; REPRESENTATION;

D O I：

10.3390/s23094258

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

The paper presents a comprehensive overview of intelligent video analytics and human action recognition methods. The article provides an overview of the current state of knowledge in the field of human activity recognition, including various techniques such as pose-based, tracking-based, spatio-temporal, and deep learning-based approaches, including visual transformers. We also discuss the challenges and limitations of these techniques and the potential of modern edge AI architectures to enable real-time human action recognition in resource-constrained environments.

引用

页数：31

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