Results 51 to 60 of about 2,293,223 (269)

A Review of Human Activity Recognition Methods

Frontiers in Robotics and AI, 2015
Recognizing human activities from video sequences or still images is a challenging task due to problems such as background clutter, partial occlusion, changes in scale, viewpoint, lighting, and appearance.
Michalis eVrigkas, Christophoros eNikou, Ioannis eKakadiaris   +2 more
doaj   +1 more source

MediaPipe with GNN for Human Activity Recognition [PDF]

Journal of Universal Computer Science
Human interaction and computer vision converge in the realm of Human Activity Recognition (HAR), which is a research field dedicated to the creation of automated systems capable of observing and categorizing human activities.
Nozha Jlidi, Sameh Kouni, Olfa Jemai, Tahani Bouchrika   +3 more
doaj   +3 more sources

Web-based visualisation of head pose and facial expressions changes: monitoring human activity using depth data

, 2016
Despite significant recent advances in the field of head pose estimation and facial expression recognition, raising the cognitive level when analysing human activity presents serious challenges to current concepts.
Kalliatakis, Grigorios, Triantafyllidis, Georgios, Vidakis, Nikolaos   +2 more
core   +1 more source

3D Human Activity Recognition with Reconfigurable Convolutional Neural Networks

, 2015
Human activity understanding with 3D/depth sensors has received increasing attention in multimedia processing and interactions. This work targets on developing a novel deep model for automatic activity recognition from RGB-D videos.
Lin, Liang, Wang, Keze, Wang, Meng, Wang, Xiaolong, Zuo, Wangmeng   +4 more
core   +1 more source

Human Activity Recognition in the Presence of Occlusion

Sensors, 2023
The presence of occlusion in human activity recognition (HAR) tasks hinders the performance of recognition algorithms, as it is responsible for the loss of crucial motion data. Although it is intuitive that it may occur in almost any real-life environment, it is often underestimated in most research works, which tend to rely on datasets that have been ...
Ioannis Vernikos, Theodoros Spyropoulos, Evaggelos Spyrou, Phivos Mylonas   +3 more
openaire   +3 more sources

Real‐World Pediatric Blinatumomab Administration: Access to Outpatient Care Delivery and Impact of a Hospital‐Dispensed Model

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Blinatumomab has been shown to be highly effective for patients with pediatric B‐ALL and has recently become standard of care therapy. Due to its past use in the clinical trial setting, there is limited information available about real‐world administration.
Katelyn Oranges, Kelly A. Duffy, Sara McDonough, Evelyn Kurpiewski, R. Jennifer Randall, Allison Barz Leahy, Haley M. Newman, Joyce P. Lee, Stephen P. Hunger, Anne F. Reilly, David T. Teachey, Susan R. Rheingold, Daniel J. Zheng   +12 more
wiley   +1 more source

Multi-Camera-Based Human Activity Recognition for Human–Robot Collaboration in Construction

Sensors, 2023
As the use of construction robots continues to increase, ensuring safety and productivity while working alongside human workers becomes crucial. To prevent collisions, robots must recognize human behavior in close proximity. However, single, or RGB-depth
Youjin Jang, Inbae Jeong, Moein Younesi Heravi, Sajib Sarkar, Hyunkyu Shin, Yonghan Ahn   +5 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  

A Probabilistic Logic Programming Event Calculus

, 2013
We present a system for recognising human activity given a symbolic representation of video content. The input of our system is a set of time-stamped short-term activities (STA) detected on video frames.
ALEXANDER ARTIKIS, ANASTASIOS SKARLATIDIS, Artikis, Biswas, Brendel, Bruynooghe, Cugola, Fierens, GEORGIOS PALIOURAS, Helaoui, JASON FILIPPOU, Kembhavi, Kosmopoulos, Lafferty, Luckham, Moldovan, Morariu, Natarajan, Sadilek, Selman, Shet, Shet, Siskind, Skarlatidis, Tran, Vail, Wang, Wu   +27 more
core   +1 more source

Ensemble learning for human activity recognition [PDF]

Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers, 2020
This paper describes a activity recognition method for Sussex-Huawei Locomotion (SHL) Challenge 2020 by team TDU_BSA. The use of ensemble learning, which combines the outputs of multiple classifiers to produce a single estimation result, improved the accuracy of activity recognition.
Ryoichi Sekiguchi, Kenji Abe, Takumi Yokoyama, Masayasu Kumano, Masaki Kawakatsu   +4 more
openaire   +1 more source