Performance of optical flow techniques
International Journal of Computer Vision
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Tracking and modeling people in video sequences
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Robot Vision
Image and Video Compression Standards: Algorithms and Architectures
Image and Video Compression Standards: Algorithms and Architectures
Spatio-temporal view interpolation
EGRW '02 Proceedings of the 13th Eurographics workshop on Rendering
Dynamic 3-D Scene Analysis Through Synthesis Feedback Control
IEEE Transactions on Pattern Analysis and Machine Intelligence
Polyhedral Visual Hulls for Real-Time Rendering
Proceedings of the 12th Eurographics Workshop on Rendering Techniques
3-D model-based tracking of humans in action: a multi-view approach
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Tracking People with Twists and Exponential Maps
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Combining 2D Feature Tracking and Volume Reconstruction for Online Video-Based Human Motion Capture
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
3D Articulated Models and Multi-View Tracking with Silhouettes
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Free-viewpoint video of human actors
ACM SIGGRAPH 2003 Papers
Continuous capture of skin deformation
ACM SIGGRAPH 2003 Papers
Constructing Virtual Worlds Using Dense Stereo
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Enhancing Silhouette-Based Human Motion Capture with 3D Motion Fields
PG '03 Proceedings of the 11th Pacific Conference on Computer Graphics and Applications
IEEE Transactions on Circuits and Systems for Video Technology
Using optical flow for step size initialisation in hand tracking by stochastic optimisation
VisHCI '06 Proceedings of the HCSNet workshop on Use of vision in human-computer interaction - Volume 56
Spatio-temporal reflectance sharing for relightable 3D video
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
3D hand tracking in a stochastic approximation setting
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animation
Multi-camera tracking of articulated human motion using motion and shape cues
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
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In recent years, the convergence of computer vision and computer graphics has put forth a new field of research that focuses on the reconstruction of real-world scenes from video streams. To make immersive 3D video reality, the whole pipeline spanning from scene acquisition over 3D video reconstruction to real-time rendering needs to be researched. In this paper, we describe latest advancements of our system to record, reconstruct and render free-viewpoint videos of human actors. We apply a silhouette-based non-intrusive motion capture algorithm making use of a 3D human body model to estimate the actor's parameters of motion from multi-view video streams. A renderer plays back the acquired motion sequence in real-time from any arbitrary perspective. Photo-realistic physical appearance of the moving actor is obtained by generating time-varying multi-view textures from video. This work shows how the motion capture sub-system can be enhanced by incorporating texture information from the input video streams into the tracking process. 3D motion fields are reconstructed from optical flow that are used in combination with silhouette matching to estimate pose parameters. We demonstrate that a high visual quality can be achieved with the proposed approach and validate the enhancements caused by the the motion field step.