A New Relational Geometric Feature for Human Action Recognition

Vinagre, Manuel; Aranda, Joan; Casals, Alı́cia

doi:10.1007/978-3-319-10891-9_15

Cited by 11 publications

(3 citation statements)

References 19 publications

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“…Prevailing feature extraction methods include Harris, SIFT, SURF, LBF, HOG, etc. Vinegar et al proposed a new set of corresponding relations among joints (Trisarea feature) [2] , which is defined as the area of triangles formed by the three joints. It could be used to recognize relevant triangles which describe human poses, and show changes in the selected Trisarea features over time so as to constitute the descriptors of human actions.…”

Section: Traditional Manual Feature Extraction Methodsmentioning

confidence: 99%

Research on Human Action Analysis and Recognition Methods Based on Deep Learning

2023

AJETS

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With the vigorous development of the Internet and multimedia technology and the large-scale popularization of video capture devices such as smartphones and surveillance cameras, video data has shown explosive growth. The goal of action recognition is to recognize the action being performed by the human in a video. As a basic but extremely challenging task in computer vision, it has a broad application prospect in many fields, such as human-machine interaction, virtual reality, intelligent video surveillance, and social public security. In this paper, human action analysis and recognition methods based on deep learning are summarized, and several prevailing action recognition algorithms are introduced and categorized in detail. Different from the traditional classification methods, we survey the currently popular algorithms into 2 series from the perspective of feature fusion: 2D convolutional series based action recognition algorithms and 3D convolutional series based action recognition algorithms.

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Section: Traditional Manual Feature Extraction Methodsmentioning

confidence: 99%

Research on Human Action Analysis and Recognition Methods Based on Deep Learning

2023

AJETS

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“…Some works directly explored the neighboring properties. For example, the authors in [135] proposed a geometric correspondence feature named the Trisarea feature. It describes neighboring properties between human body joints and is defined as the area of the triangle formed by three joints.…”

Section: Generalized Geometrics For Human-related Analysismentioning

confidence: 99%

A Literature Review: Geometric Methods and Their Applications in Human-Related Analysis

Gong

Zhang

Wang

et al. 2019

Sensors

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Geometric features, such as the topological and manifold properties, are utilized to extract geometric properties. Geometric methods that exploit the applications of geometrics, e.g., geometric features, are widely used in computer graphics and computer vision problems. This review presents a literature review on geometric concepts, geometric methods, and their applications in human-related analysis, e.g., human shape analysis, human pose analysis, and human action analysis. This review proposes to categorize geometric methods based on the scope of the geometric properties that are extracted: object-oriented geometric methods, feature-oriented geometric methods, and routine-based geometric methods. Considering the broad applications of deep learning methods, this review also studies geometric deep learning, which has recently become a popular topic of research. Validation datasets are collected, and method performances are collected and compared. Finally, research trends and possible research topics are discussed.

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“…When dealing with daily live activities, gesture and activity recognition aiming to interpret the user's will, or their needs, allows the generation of robot actuation strategies in a proactive way [1] [2]. These proactive strategies may even require the interaction of multiple robots, when more than one arm is needed to accomplish a given task Vinagre, M.; Aranda, J.; Casals, A.…”

Section: Introductionmentioning

confidence: 99%

Suitable Task Allocation in Intelligent Systems for Assistive Environments

Vinagre

Aranda

Casals

2019

Advances in Intelligent Systems and Computing

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The growing need of technological assistance to provide support to people with special needs demands for systems more and more efficient and with better performances. With this aim, this work tries to advance in a multirobot platform that allows the coordinated control of different agents and other elements in the environment to achieve an autonomous behavior based on the user's needs or will. Therefore, this environment is structured according to the potentiality of each agent and elements of this environment and of the dynamic context, to generate the adequate actuation plans and the coordination of their execution.

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A New Relational Geometric Feature for Human Action Recognition

Cited by 11 publications

References 19 publications

Research on Human Action Analysis and Recognition Methods Based on Deep Learning

Research on Human Action Analysis and Recognition Methods Based on Deep Learning

A Literature Review: Geometric Methods and Their Applications in Human-Related Analysis

Suitable Task Allocation in Intelligent Systems for Assistive Environments

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