An elliptical modeling supported system for human action deep recognition over aerial surveillance
The advancement of computer vision technology has led to the development of
sophisticated algorithms capable of accurately recognizing human actions from red-green …
sophisticated algorithms capable of accurately recognizing human actions from red-green …
Aerial insights: Deep learning-based human action recognition in drone imagery
Human action recognition is critical because it allows machines to comprehend and interpret
human behavior, which has several real-world applications such as video surveillance …
human behavior, which has several real-world applications such as video surveillance …
Progress of human action recognition research in the last ten years: a comprehensive survey
Abstract Human Action Recognition (HAR) has achieved a remarkable milestone in the field
of computer vision. Apart from its varied applications in human–computer interactions …
of computer vision. Apart from its varied applications in human–computer interactions …
Depth sensors-based action recognition using a modified K-ary entropy classifier
Surveillance system is acquiring an ample interest in the field of computer vision. Existing
surveillance system usually relies on optical or wearable sensors for indoor and outdoor …
surveillance system usually relies on optical or wearable sensors for indoor and outdoor …
[PDF][PDF] Drone-Based Video Surveillance Using YOLOv6 and Neuro-Fuzzy Classifier
The rise of computer vision technology has seen development of advanced algorithms that
can accurately detect human activities from RGB videos taken by drone cameras. One major …
can accurately detect human activities from RGB videos taken by drone cameras. One major …
3dfcnn: Real-time action recognition using 3d deep neural networks with raw depth information
This work describes an end-to-end approach for real-time human action recognition from
raw depth image-sequences. The proposal is based on a 3D fully convolutional neural …
raw depth image-sequences. The proposal is based on a 3D fully convolutional neural …
Semantic recognition of human-object interactions via Gaussian-based elliptical modeling and pixel-level labeling
Human-Object Interaction (HOI) recognition, due to its significance in many computer vision-
based applications, requires in-depth and meaningful details from image sequences …
based applications, requires in-depth and meaningful details from image sequences …
Features extraction from multi-spectral remote sensing images based on multi-threshold binarization
In this paper, we propose a solution to resolve the limitation of deep CNN models in real-
time applications. The proposed approach uses multi-threshold binarization over the whole …
time applications. The proposed approach uses multi-threshold binarization over the whole …
Improved human action recognition approach based on two-stream convolutional neural network model
C Liu, J Ying, H Yang, X Hu, J Liu - The visual computer, 2021 - Springer
In order to improve the accuracy of human abnormal behavior recognition, a two-stream
convolution neural network model was proposed. This model includes two main parts, VMHI …
convolution neural network model was proposed. This model includes two main parts, VMHI …
Towards a deep human activity recognition approach based on video to image transformation with skeleton data
One of the most recent challenging tasks in computer vision is Human Activity Recognition
(HAR), which aims to analyze and detect the human actions for the benefit of many fields …
(HAR), which aims to analyze and detect the human actions for the benefit of many fields …