We introduce DeMoCap, the first data-driven approach for end-to-end marker-based MoCap, using only a sparse setup of spatio-temporally aligned, consumer-grade infrared-depth cameras. Trading off some of their typical features, our approach is the sole robust option for far lower-cost marker-...
DeMoCap: Low-Cost Marker-Based Motion Capture作者:Anargyros Chatzitofis, Dimitrios Zarpalas, Petros Daras, Stefanos Kollias摘要 Optical marker-based motion capture (MoCap) remains the predominant way to acquire high-fidelity articulated body motions. We introduce DeMoCap, the first data-driven appr...
DeepMoCap Github page: mocap fully-convolutional-networks marker-based Updated Jun 6, 2019 C# aknj / ar Star 2 Code Issues Pull requests marker-based augmented reality computer-vision augmented-reality marker-based Updated Jun 10, 2020 C++ ...
The MirrorMoCap system by Lin and Ouhyoung (Lin & Ouhyoung, 2005) uses more than 300 fluorescent markers and a mirror system to accurately track the shape of the face. The use of the mirror system allows a wider angle of the face to be captured with a single camera. The system opera...
As MOCAP systems evolved, a higher number of poin...Alexander, E., Andriacchi, T. (2001). Correcting for deformation in skin-based mar- ker systems. Journal of Biomechanics, 34, 355-361.Reiter, R. 2001. PCR-based marker systems. DNA-based markers in plants (2nd ed). Kluwer Academic...
Video-based, markerless, mocap systems are, in some cases, replacing marker-based systems, but hybrid systems are less explored. We develop methods for coregistration between 2D video and 3D marker positions when precise spatial relationships are not known a priori. We illustrate these method...
Infrared marker-based motion capture systems (MoCap) have been developed to track continuous motion in 3D space [5]. Due to their high level of precision, infrared marker-based systems are considered the gold standard in modern gait analysis [6] and, in general, in accurate tracking of human...
Infrared marker-based motion capture systems (MoCap) have been developed to track continuous motion in 3D space [5]. Due to their high level of precision, infrared marker-based systems are considered the gold standard in modern gait analysis [6] and, in general, in accurate tracking of human...
DEEP learningATHLETIC abilityARTIFICIAL intelligenceMotion capture (MoCap) technology, essential for biomechanics and motion analysis, faces challenges from data loss due to occlusions and technical issues. Traditional recovery methods, based on inter-marker relationships or independent marker treatment, have ...
This study introduces a novel U-net-inspired bi-directional long short-term memory (U-Bi-LSTM) autoencoder-based technique for recovering missing MoCap data across multi-camera setups. Leveraging multi-camera and triangulated 3D data, this method employs a sophisticated U-shaped deep learning ...