Results 161 to 170 of about 8,152 (183)

Markerless 3D facial motion capture system

SPIE Proceedings, 2012
We propose a novel markerless 3D facial motion capture system using only one common camera. This system is simple and easy to transfer facial expressions of a user's into virtual world. It has robustly tracking facial feature points associated with head movements. In addition, it estimates high accurate 3D points' locations.
Youngkyoo Hwang, Jung-Bae Kim, Xuetao Feng, Won-Chul Bang, Taehyun Rhee, James D.K. Kim, ChangYeong Kim   +6 more
openaire   +1 more source

Markerless motion capture using appearance and inertial data

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014
Current monitoring techniques for biomechanical analysis typically capture a snapshot of the state of the subject due to challenges associated with long-term monitoring. Continuous long-term capture of biomechanics can be used to assess performance in the workplace and rehabilitation at home.
Charence, Wong, Zhiqiang, Zhang, Benny, Lo, Guang-Zhong, Yang   +3 more
openaire   +2 more sources

Gait Recognition from Markerless 3D Motion Capture

2019 International Conference on Biometrics (ICB), 2019
State of the art gait recognition methods often make use of the shape of the body as well as its movement, as observed in the use of Gait Energy Images(GEIs), for recognition. However, it is desirable to have a method that works exclusively with the movement of the body, as clothing and other factors may interfere with the biometric signature from body
James Rainey, John Bustard, Seán McLoone   +2 more
openaire   +1 more source

Online Smoothing for Markerless Motion Capture

2007
Tracking 3D objects from 2D image data often leads to jittery tracking results. In general, unsmooth motion is a sign of tracking errors, which, in the worst case, can cause the tracker to loose the tracked object. A straightforward remedy is to demand temporal consistency and to smooth the result. This is often done in form of a post-processing.
Rosenhahn, B., Brox, T., Cremers, D., Seidel, H. ; https://orcid.org/0000-0002-1343-8613   +3 more
openaire   +2 more sources

Markerless human motion capture and pose recognition

2009 10th Workshop on Image Analysis for Multimedia Interactive Services, 2009
In this paper, we present an approach to capture markerless human motion and recognize human poses. Different body parts such as the torso and the hands are segmented from the whole body and tracked over time. A 2D model is used for the torso detection and tracking, while a skin color model is utilized for the hands tracking.
Feifei Huo, Emile Hendriks, Pavel Paclik, A.H.J. Oomes   +3 more
openaire   +1 more source

Anatomical-Marker-Driven 3D Markerless Human Motion Capture

IEEE Journal of Biomedical and Health Informatics
Marker-based motion capture (mocap) is a conventional method used in biomechanics research to precisely analyze human movement. However, the time-consuming marker placement process and extensive post-processing limit its wider adoption. Therefore, markerless mocap systems that use deep learning to estimate 2D keypoint from images have emerged as a ...
Prayook Jatesiktat, Guan Ming Lim, Wee Sen Lim, Wei Tech Ang   +3 more
openaire   +2 more sources

Outdoor Markerless Motion Capture with Sparse Handheld Video Cameras

IEEE Transactions on Visualization and Computer Graphics, 2018
We present a method for outdoor markerless motion capture with sparse handheld video cameras. In the simplest setting, it only involves two mobile phone cameras following the character. This setup can maximize the flexibilities of data capture and broaden the applications of motion capture.
Yangang Wang, Yebin Liu, Xin Tong, Qionghai Dai, Ping Tan   +4 more
openaire   +3 more sources

Experimenting with noise in markerless motion capture

Proceedings of the 2nd International Workshop on Movement and Computing, 2015
Visual culture has embraced the visual glitch as just one of many aesthetics associated with digital media. A glitch is often associated with noise in a technological system. Some motion capture systems experience noise and glitches as they process human movement.
openaire   +1 more source

Markerless motion capture: the challenge of accuracy in capturing animal motions through model based approaches

SPIE Proceedings, 2009
In the paper the application of model based markerless motion capture technology to general environment and quadrupeds is presented. Some of the authors' recent results are discussed together with the open challenges related to the capture of animal motion. Despite its very recent history, markerless motion capture represents already both a valuable
GAMBARETTO, EMILIANO, S. Corazza
openaire   +2 more sources

Markerless motion capture with single and multiple cameras

2004 International Conference on Image Processing, 2004. ICIP '04., 2005
The aim of optical motion capture is to sequentially estimate the true state X of the subject (generally an articulated body) at any time instant t/sub k/ from a set of data D/sub k/, captured by N calibrated cameras each of resolution U/spl times/V pixels. Our aim is to achieve this without the need for markers.
P. Kaimakis, J. Lasenby
openaire   +1 more source