Human action recognition from various data modalities: A review
Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …
each action. It has a wide range of applications, and therefore has been attracting increasing …
3D point cloud data processing with machine learning for construction and infrastructure applications: A comprehensive review
Point clouds are increasingly being used to improve productivity, quality, and safety
throughout the life cycle of construction and infrastructure projects. While applicable for …
throughout the life cycle of construction and infrastructure projects. While applicable for …
Object classification using CNN-based fusion of vision and LIDAR in autonomous vehicle environment
This paper presents an object classification method for vision and light detection and
ranging (LIDAR) fusion of autonomous vehicles in the environment. This method is based on …
ranging (LIDAR) fusion of autonomous vehicles in the environment. This method is based on …
Deep learning pipelines for recognition of gait biometrics with covariates: a comprehensive review
This paper presents a comprehensive exposition of deep learning architectures and
pipelines for biometric applications using complex characteristics of human gait. The variety …
pipelines for biometric applications using complex characteristics of human gait. The variety …
Hamlet: A hierarchical multimodal attention-based human activity recognition algorithm
To fluently collaborate with people, robots need the ability to recognize human activities
accurately. Although modern robots are equipped with various sensors, robust human …
accurately. Although modern robots are equipped with various sensors, robust human …
Combining CNN streams of RGB-D and skeletal data for human activity recognition
Inspired by the success of deep learning methods, for human activity recognition based on
individual vision cues, this paper presents a ConvNets based approach for activity …
individual vision cues, this paper presents a ConvNets based approach for activity …
Multi-gat: A graphical attention-based hierarchical multimodal representation learning approach for human activity recognition
Recognizing human activities is one of the crucial capabilities that a robot needs to have to
be useful around people. Although modern robots are equipped with various types of …
be useful around people. Although modern robots are equipped with various types of …
Exploring a rich spatial–temporal dependent relational model for skeleton-based action recognition by bidirectional LSTM-CNN
With the fast development of effective and low-cost human skeleton capture systems,
skeleton-based action recognition has attracted much attention recently. Most existing …
skeleton-based action recognition has attracted much attention recently. Most existing …
Mumu: Cooperative multitask learning-based guided multimodal fusion
Multimodal sensors (visual, non-visual, and wearable) can provide complementary
information to develop robust perception systems for recognizing activities accurately …
information to develop robust perception systems for recognizing activities accurately …
Video benchmarks of human action datasets: a review
Vision-based Human activity recognition is becoming a trendy area of research due to its
wide application such as security and surveillance, human–computer interactions, patients …
wide application such as security and surveillance, human–computer interactions, patients …