Results 41 to 50 of about 2,923,075 (185)

Through-wall Human Pose Reconstruction and Action Recognition Using Four-dimensional Imaging Radar

Leida xuebao
Through-wall human pose reconstruction and behavior recognition have enormous potential in fields like intelligent security and virtual reality. However, existing methods for through-wall human sensing often fail to adequately model four-Dimensional (4D)
Rui ZHANG, Hanqin GONG, Ruiyuan SONG, Yadong LI, Zhi LU, Dongheng ZHANG, Yang HU, Yan CHEN   +7 more
doaj   +1 more source

Recognition of Daily and Sports Activities

2018 IEEE International Conference on Big Data (Big Data), 2018
Since being physically inactive was reported as one of the major risk factor of mortality, classifying daily and sports activities becomes a critical task that may improve human life quality. In this paper, the daily and sports activities dataset was used in order to evaluate and validate the employed approach.
Inanç N., Kayri M., Ertu?rul O.F.
openaire   +4 more sources

Tangible User Interface and Mu Rhythm Suppression: The Effect of User Interface on the Brain Activity in Its Operator and Observer

Applied Sciences, 2017
The intuitiveness of tangible user interface (TUI) is not only for its operator. It is quite possible that this type of user interface (UI) can also have an effect on the experience and learning of observers who are just watching the operator using it ...
Kazuo Isoda, Kana Sueyoshi, Ryo Miyamoto, Yuki Nishimura, Yuki Ikeda, Ichiro Hisanaga, Stéphanie Orlic, Yeon-kyu Kim, Shigekazu Higuchi   +8 more
doaj   +1 more source

Latent Embeddings for Collective Activity Recognition

, 2017
Rather than simply recognizing the action of a person individually, collective activity recognition aims to find out what a group of people is acting in a collective scene. Previ- ous state-of-the-art methods using hand-crafted potentials in conventional
Hu, Jian-Fang, Tang, Yongyi, Zhang, Peizhen, Zheng, Wei-Shi   +3 more
core   +1 more source

Generalized Rank Pooling for Activity Recognition

, 2017
Most popular deep models for action recognition split video sequences into short sub-sequences consisting of a few frames; frame-based features are then pooled for recognizing the activity.
Cherian, Anoop, Fernando, Basura, Gould, Stephen, Harandi, Mehrtash   +3 more
core   +1 more source

Going Deeper into First-Person Activity Recognition

, 2016
We bring together ideas from recent work on feature design for egocentric action recognition under one framework by exploring the use of deep convolutional neural networks (CNN).
Fan, Haoqi, Kitani, Kris M., Ma, Minghuang   +2 more
core   +1 more source

A Multi-Agent and Attention-Aware Enhanced CNN-BiLSTM Model for Human Activity Recognition for Enhanced Disability Assistance

Diagnostics
Background: Artificial intelligence (AI)-based automated human activity recognition (HAR) is essential in enhancing assistive technologies for disabled individuals, focusing on fall detection, tracking rehabilitation progress, and analyzing personalized ...
Mst Alema Khatun, Mohammad Abu Yousuf, Taskin Noor Turna, AKM Azad, Salem A. Alyami, Mohammad Ali Moni   +5 more
doaj   +1 more source

On-Device Deep Personalization for Robust Activity Data Collection

Sensors, 2020
One of the biggest challenges of activity data collection is the need to rely on users and keep them engaged to continually provide labels. Recent breakthroughs in mobile platforms have proven effective in bringing deep neural networks powered ...
Nattaya Mairittha, Tittaya Mairittha, Sozo Inoue   +2 more
doaj   +1 more source

Early Recognition of Human Activities from First-Person Videos Using Onset Representations [PDF]

, 2015
In this paper, we propose a methodology for early recognition of human activities from videos taken with a first-person viewpoint. Early recognition, which is also known as activity prediction, is an ability to infer an ongoing activity at its early ...
Aggarwal, J. K., Fuchs, Thomas J., Matthies, Larry, Ryoo, M. S., Xia, Lu   +4 more
core  

Human Activity Recognition [PDF]

, 2005
Motion is an important cue for the human visual system Mobiles have fascinated children, Zeno (circa 500 B.C.) studied moving arrows to pose a paradox and Zeke is investigating the human brain devoted to the understanding of motion. In computer vision research, motion has played an important role for the past thirty years.
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