Cartoon Motion Capturing and Retargeting by Rigid Shape Manipulation

2009 ◽  
Author(s):  
Mohammad Rastegari ◽  
Mohammad Rouhani ◽  
Niloofar Gheissari ◽  
Mir Mohsen Pedram
Keyword(s):  
Motion Capturing ◽  
Shape Manipulation

scholarly journals A Motion Capturing and Energy Harvesting Hybridized Lower‐Limb System for Rehabilitation and Sports Applications

2021 ◽  
pp. 2101834
Author(s):  
Shan Gao ◽  
Tianyiyi He ◽  
Zixuan Zhang ◽  
Hongrui Ao ◽  
Hongyuan Jiang ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Lower Limb ◽  
Motion Capturing

Structure-from-Motion, Capturing Geological Samples v1

2021 ◽  
Author(s):  
Madalyn Massey
Keyword(s):  
United States ◽  
Structure From Motion ◽  
3D Models ◽  
Geological Survey ◽  
United States Geological Survey ◽  
Geological Samples ◽  
Motion Capturing ◽  
2D Images

Structure-from-Motion (SfM) is a photogrammetry process that creates 3D models from overlapping 2D images. This protocol focuses on its application related to geological and geophysical samples. The samples includes fossil, hand samples and rocks. This is a recommended practice to be used later for the publication on United States Geological Survey website.

scholarly journals Context-Aware Human Activity Recognition in Industrial Processes

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 134
Author(s):  
Friedrich Niemann ◽  
Stefan Lüdtke ◽  
Christian Bartelt ◽  
Michael ten Hompel
Keyword(s):  
Activity Recognition ◽  
Time Management ◽  
Recognition Performance ◽  
Context Information ◽  
Context Aware ◽  
Recognition Model ◽  
Movement Data ◽  
Information Activity ◽  
The Subject ◽  
Motion Capturing

The automatic, sensor-based assessment of human activities is highly relevant for production and logistics, to optimise the economics and ergonomics of these processes. One challenge for accurate activity recognition in these domains is the context-dependence of activities: Similar movements can correspond to different activities, depending on, e.g., the object handled or the location of the subject. In this paper, we propose to explicitly make use of such context information in an activity recognition model. Our first contribution is a publicly available, semantically annotated motion capturing dataset of subjects performing order picking and packaging activities, where context information is recorded explicitly. The second contribution is an activity recognition model that integrates movement data and context information. We empirically show that by using context information, activity recognition performance increases substantially. Additionally, we analyse which of the pieces of context information is most relevant for activity recognition. The insights provided by this paper can help others to design appropriate sensor set-ups in real warehouses for time management.

3D Human Motion Capturing Based Only on Acceleration and Angular Rate Measurement for Low Extremities

2011 ◽  
pp. 195-203 ◽  
Author(s):  
Christoph Schiefer ◽  
Thomas Kraus ◽  
Elke Ochsmann ◽  
Ingo Hermanns ◽  
Rolf Ellegast
Keyword(s):  
Angular Rate ◽  
Human Motion ◽  
Rate Measurement ◽  
Motion Capturing

scholarly journals Inertial measurement unit compared to an optical motion capturing system in post-stroke individuals with foot-drop syndrome

2020 ◽  
Vol 63 (3) ◽  
pp. 195-201 ◽  
Author(s):  
François Feuvrier ◽  
Benoît Sijobert ◽  
Christine Azevedo ◽  
Karolina Griffiths ◽  
Sandrine Alonso ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Foot Drop ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Post Stroke ◽  
Optical Motion ◽  
Motion Capturing
Sign in / Sign up

Export Citation Format

Share Document