A survey on deep learning for human activity recognition
Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …
home. In this study, we provide a comprehensive survey on recent advances and challenges …
First-person hand action benchmark with rgb-d videos and 3d hand pose annotations
G Garcia-Hernando, S Yuan… - Proceedings of the …, 2018 - openaccess.thecvf.com
In this work we study the use of 3D hand poses to recognize first-person dynamic hand
actions interacting with 3D objects. Towards this goal, we collected RGB-D video sequences …
actions interacting with 3D objects. Towards this goal, we collected RGB-D video sequences …
A survey on activity detection and classification using wearable sensors
Activity detection and classification are very important for autonomous monitoring of humans
for applications, including assistive living, rehabilitation, and surveillance. Wearable sensors …
for applications, including assistive living, rehabilitation, and surveillance. Wearable sensors …
Trear: Transformer-based rgb-d egocentric action recognition
In this article, we propose a transformer-based RGB-D egocentric action recognition
framework, called Trear. It consists of two modules: 1) interframe attention encoder and 2) …
framework, called Trear. It consists of two modules: 1) interframe attention encoder and 2) …
Sensors in assisted living: A survey of signal and image processing methods
Our society will face a notable demographic shift in the near future. According to a United
Nations report, the ratio of the elderly population (aged 60 years or older) to the overall …
Nations report, the ratio of the elderly population (aged 60 years or older) to the overall …
[HTML][HTML] Meccano: A multimodal egocentric dataset for humans behavior understanding in the industrial-like domain
Wearable cameras allow to acquire images and videos from the user's perspective. These
data can be processed to understand humans behavior. Despite human behavior analysis …
data can be processed to understand humans behavior. Despite human behavior analysis …
Multi-stream deep neural networks for rgb-d egocentric action recognition
In this paper, we investigate the problem of RGB-D egocentric action recognition. Unlike
conventional human action videos that are passively recorded by static cameras, egocentric …
conventional human action videos that are passively recorded by static cameras, egocentric …
Adaptive feature processing for robust human activity recognition on a novel multi-modal dataset
M Moencks, V De Silva, J Roche, A Kondoz - arXiv preprint arXiv …, 2019 - arxiv.org
Human Activity Recognition (HAR) is a key building block of many emerging applications
such as intelligent mobility, sports analytics, ambient-assisted living and human-robot …
such as intelligent mobility, sports analytics, ambient-assisted living and human-robot …
Action recognition in RGB-D egocentric videos
In this paper, we investigate the problem of action recognition in RGB-D egocentric videos.
These self-generated and embodied videos provide richer semantic cues than the …
These self-generated and embodied videos provide richer semantic cues than the …
Egocentric scene understanding via multimodal spatial rectifier
In this paper, we study a problem of egocentric scene understanding, ie, predicting depths
and surface normals from an egocentric image. Egocentric scene understanding poses …
and surface normals from an egocentric image. Egocentric scene understanding poses …