scholarly journals Realistic synthesis of novel human movements from a database of motion capture examples

2002 ◽  
Author(s):  
L.M. Tanco ◽  
A. Hilton
Keyword(s):  
Motion Capture ◽  
Human Movements

scholarly journals Dance motion capture and composition using multiple RGB and depth sensors

2017 ◽  
Vol 13 (2) ◽  
pp. 155014771769608 ◽  
Author(s):  
Yejin Kim
Keyword(s):  
Motion Capture ◽  
High Speed ◽  
Motion Path ◽  
High Complexity ◽  
Motion Data ◽  
Depth Sensors ◽  
Motion Editing ◽  
Human Movements ◽  
Marker Free ◽  
Motion Search

Dynamic human movements such as dance are difficult to capture without using external markers due to the high complexity of a dancer’s body. This article introduces a marker-free motion capture and composition system for dance motion that uses multiple RGB and depth sensors. Our motion capture system utilizes a set of high-speed RGB and depth sensors to generate skeletal motion data from an expert dancer. During the motion acquisition process, a skeleton tracking method based on a particle filter is provided to estimate the motion parameters for each frame from a sequence of color images and depth features retrieved from the sensors. The expert motion data become archived in a database. The authoring methods in our composition system automate most of the motion editing processes for general users by providing an online motion search with an input posture and then performing motion synthesis on an arbitrary motion path. Using the proposed system, we demonstrate that various dance performances can be composed in an intuitive and efficient way on client devices such as tablets and kiosk PCs.

scholarly journals Digital Technologies and Virtual Worlds: Is Mankind on the Threshold of New Art?

2010 ◽  
Vol 2 (2) ◽  
pp. 192-203
Author(s):  
Elena Georgievna Yaremenko ◽  
Yelena Georgievna Yaremenko
Keyword(s):  
Computer Graphics ◽  
Motion Capture ◽  
Virtual Worlds ◽  
3D Model ◽  
Computer Software ◽  
Digital Technologies ◽  
Special Effects ◽  
Virtual Characters ◽  
Human Movements

The digital special effects industry is constantly in development and in search of new expressive means. The more and more popular 3D computer graphics can mold characters and objects similar to puppet animation but more detailed and convincing. Computer software makes it possible to fix human movements and create virtual characters. By means of the motion capture technology reflecting the subtlest shades of human plastique the computer catches the movements of the sensors fixed to the actor's face and body, analyzes the data and applies it the 3D model. As a result, screen characters behave like live people. As far as the audience is concerned, there is practically no difference between the reality recorded on film, video or photo, and that created by the artist's imagination with the help of the computer on the modern screen

Motion Capture for Human-Centered Simulation Using Kinects

2013 ◽  
Author(s):  
Chinmay P. Daphalapurkar ◽  
Wenjuan Zhu ◽  
Ming C. Leu ◽  
Xiaoqing F. Liu ◽  
Alpha M. Chang ◽  
...  
Keyword(s):  
Motion Capture ◽  
Low Cost ◽  
Microsoft Kinect ◽  
Frame Rate ◽  
Infrared Light ◽  
Aircraft Fuselage ◽  
Light Pattern ◽  
Human Movements ◽  
Shutter Mechanism ◽  
Motion Capture Systems

Microsoft Kinect is capable of tracking human movements and can be used to develop various human-centered simulations. It is very attractive for certain applications because it is a low-cost, marker-less device. This paper presents our research toward characterizing the accuracy of Kinect and developing Kinect-based motion capture systems. Besides a single-Kinect system, a motion capture system with multiple Kinects were developed in order to increase the tracking volume and to improve the simulation fidelity. A motor-driven shutter mechanism was developed for use with each Kinect for the multi-Kinect system to address the issue of interference on the infrared light pattern without lowering the frame rate. The capabilities of the developed Kinect-based motion capture systems are demonstrated by tracking a human in performing a fastening operation on an aircraft fuselage mockup.

scholarly journals Wide Area Motion Tracking Using Consumer Hardware

2013 ◽  
Vol 12 (1) ◽  
pp. 57-65
Author(s):  
Christian Schönauer ◽  
Hannes Kaufmann
Keyword(s):  
Motion Capture ◽  
Local Area Network ◽  
Tracking System ◽  
Local Area ◽  
Wide Area ◽  
Area Network ◽  
Skeleton Model ◽  
Pose Tracking ◽  
Human Movements ◽  
Human Pose

In this paper we present a wide area tracking system based on consumer hardware and available motion capture modules and middleware. We are using multiple depth cameras for human pose tracking in order to increase the captured space. Commercially available cameras can capture human movements in a non-intrusive way, while associated software-modules produce pose information of a simplified skeleton model. We calibrate the cameras relatively to each other to seamlessly combine their tracking data. Our design allows an arbitrary number of sensors to be integrated and used in parallel over a local area network. This enables us to capture human movements in a large arbitrarily shaped area. In addition we can improve motion capture data in regions, where the field of view of multiple cameras overlaps, by mutually completing partly occluded poses. In various examples we demonstrate, how human pose data is being merged in order to cover a wide area and how this data can easily be used for character animation in a virtual environment.

Classification of Human Movements with Motion Capture Data in a Motor Rehabilitation Context

2021 ◽  
Author(s):  
Luis Guilherme Silva Rodrigues ◽  
Diego Dias ◽  
Marcelo de Paiva Guimaraes ◽  
Alexandre Fonseca Brandao ◽  
Leonardo Rocha ◽  
...  
Keyword(s):  
Motion Capture ◽  
Motion Capture Data ◽  
Motor Rehabilitation ◽  
Human Movements

scholarly journals Use of Human Motion Data to Train Wearable Robots

2021 ◽  
Vol 12 (6) ◽  
pp. 807-811
Author(s):  
JIBUM JUNG Et.al
Keyword(s):  
Motion Capture ◽  
Human Motion ◽  
Machine Learning Algorithms ◽  
Walking Robots ◽  
Motion Capture System ◽  
Motion Data ◽  
Wearable Robots ◽  
Human Movements ◽  
Optical Motion ◽  
Optical Motion Capture

Development of wearable robots is accelerating. Walking robots mimic human behavior and must operate without accidents. Human motion data are needed to train these robots. We developed a system for extracting human motion data and displaying them graphically.We extracted motion data using a Perception Neuron motion capture system and used the Unity engine for the simulation. Several experiments were performed to demonstrate the accuracy of the extracted motion data.Of the various methods used to collect human motion data, markerless motion capture is highly inaccurate, while optical motion capture is very expensive, requiring several high-resolution cameras and a large number of markers. Motion capture using a magnetic field sensor is subject to environmental interference. Therefore, we used an inertial motion capture system. Each movement sequence involved four and was repeated 10 times. The data were stored and standardized. The motions of three individuals were compared to those of a reference person; the similarity exceeded 90% in all cases. Our rehabilitation robot accurately simulated human movements: individually tailored wearable robots could be designed based on our data. Safe and stable robot operation can be verified in advance via simulation. Walking stability can be increased using walking robots trained via machine learning algorithms.

A study on validating KinectV2 in comparison of Vicon system as a motion capture system for using in Health Engineering in industry

2017 ◽  
Vol 6 (2) ◽  
Author(s):  
Mahvash Jebeli ◽  
Alireza Bilesan ◽  
Ahmadreza Arshi
Keyword(s):  
Motion Capture ◽  
Three Dimensional ◽  
Vertical Axis ◽  
Coefficient Of Determination ◽  
Motion Capture System ◽  
Kinect Sensor ◽  
3D Data ◽  
Human Movements ◽  
Analysis Laboratory ◽  
Industrial Environments

AbstractThe currently available commercial motion capture systems are constrained by space requirement and thus pose difficulties when used in developing kinematic description of human movements within the existing manufacturing and production cells. The Kinect sensor does not share similar limitations but it is not as accurate. The proposition made in this article is to adopt the Kinect sensor in to facilitate implementation of Health Engineering concepts to industrial environments. This article is an evaluation of the Kinect sensor accuracy when providing three dimensional kinematic data. The sensor is thus utilized to assist in modeling and simulation of worker performance within an industrial cell. For this purpose, Kinect 3D data was compared to that of Vicon motion capture system in a gait analysis laboratory. Results indicated that the Kinect sensor exhibited a coefficient of determination of 0.9996 on the depth axis and 0.9849 along the horizontal axis and 0.2767 on vertical axis. The results prove the competency of the Kinect sensor to be used in the industrial environments.

Correlational Methods for Analysis of Dance Movements

2011 ◽  
Vol 29 (supplement) ◽  
pp. 283-304 ◽  
Author(s):  
Timothy R. Brick ◽  
Steven M. Boker
Keyword(s):  
Motion Capture ◽  
Mirror Symmetry ◽  
Cross Correlation ◽  
The Other ◽  
Free Form ◽  
Motion Capture Data ◽  
Complex Interactions ◽  
Dance Movements ◽  
Time Lagged ◽  
Insight Into

Among the qualities that distinguish dance from other types of human behavior and interaction are the creation and breaking of synchrony and symmetry. The combination of symmetry and synchrony can provide complex interactions. For example, two dancers might make very different movements, slowing each time the other sped up: a mirror symmetry of velocity. Examining patterns of synchrony and symmetry can provide insight into both the artistic nature of the dance, and the nature of the perceptions and responses of the dancers. However, such complex symmetries are often difficult to quantify. This paper presents three methods – Generalized Local Linear Approximation, Time-lagged Autocorrelation, and Windowed Cross-correlation – for the exploration of symmetry and synchrony in motion-capture data as is it applied to dance and illustrate these with examples from a study of free-form dance. Combined, these techniques provide powerful tools for the examination of the structure of symmetry and synchrony in dance.

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