Motion capture using joint skeleton tracking and surface estimation

By Juergen Gall, Carsten Stoll, Edilson de Aguiar, Christian Theobalt, Bodo Rosenhahn, Hans-Peter Seidel. 2009

464 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering

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In Computer Vision and Pattern Recognition

In Control and Systems Engineering

Citations in the corpus

Space-Time Representation of People Based on 3D Skeletal Data: A Review (2016, methodology): “To address these problems, algorithms were also studied to construct human skeleton models directly from the multi-images without calculating the depth image [71], [72], [73].”
Dynamic FAUST: Registering Human Bodies in Motion (2017, background): “For example, there are many non-rigid tracking methods, either model-based [3, 7, 22, 25, 27, 34, 44, 49] or model-free [2, 16, 21, 24, 37, 50, 54].”
Monocular Total Capture: Posing Face, Body, and Hands in the Wild (2018, background): “The actively-studied markerless approaches are also based on multi-view systems [21, 29, 19, 25, 26] or depth cameras [50, 7].”
Coupled Action Recognition and Pose Estimation from Multiple Views (2012, unknown): “[5] 28 4 48 [4] -350 28 1 101 [71] 250 4 83 78 [56] -380 36 4 107 92 [24] 124 4 38 32 [8] 20th - 4 207 292 [13] -350 - 2 53 54 [16] -150 - 4 78 80 [66] 15 4 49 [25] -400 30 4 36 [27] 9 4 50 [17] 15-20 2-3 97 93 ap+sm 4 4 42 42 up+sm 4 4 47 42”
Expressive Body Capture: 3D Hands, Face, and Body From a Single Image (2019, unknown): “3D models [7, 20, 24, 30, 35, 46, 54, 66, 72].”
Video Based Reconstruction of 3D People Models (2018, unknown): “In [23, 69] they pre-scan a template and insert a skeleton and in [78] they use a skeleton to regularize dynamic fusion.”
PaMIR: Parametric Model-Conditioned Implicit Representation for Image-Based Human Reconstruction (2020, background): “Note also that although temporal deformation systems using lightweight camera setups [29], [30], [31] have been developed for dynamic human model reconstruction using skeleton tracking ( [29], [32]) or human mesh template deformation [30], these systems require a pre-scanned subject-speciﬁc 3D…”
Survey on Emotional Body Gesture Recognition (2018, methodology): “Using poselets for encoding the pose information was proposed in [64], [65].”
Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies (2018, background): “Markerless motion capture methods [23, 17, 21, 44] have been explored over the past two decades to achieve the same goal without markers, but they tend to implicitly admit that their performance is inferior by treating the output of marker based methods as a ground truth or an upper bound.”
Capturing the human figure through a wall (2015, background): “…– including Kinect, multi-view cameras, moving cameras, and time-of-ﬂight cameras – and require a direct line-of-sight from the sensor to the person’s body, e.g., [Shotton et al. 2013; Ganapathi et al. 2010; Hasler et al. 2009b; Gall et al. 2009; Vlasic et al. 2008; Poppe 2007; Ye et al. 2014].”
DeepHuman: 3D Human Reconstruction From a Single Image (2019, background): “Note also that although temporal deformation systems using lightweight camera setups [54, 9, 14] have been developed for dynamic human model reconstruction using skeleton tracking [54, 31] or human mesh template deformation [9], these systems assume a pre-scanned subject-specific human template as a”
Articulated and Generalized Gaussian Kernel Correlation for Human Pose Estimation (2016, methodology): “One of the most widely used shape models is the mesh surface [6], [37], [38] that is able to be deformed smoothly for articulate pose estimation.”
ARCH: Animatable Reconstruction of Clothed Humans (2020, background): “There are multiple attempts to solve this task with video inputs [2, 3, 37, 1, 52], RGB-D data [53, 56] and in multi-view settings [5, 13, 14, 45, 46, 47, 48, 6].”
Panoptic Studio: A Massively Multiview System for Social Motion Capture (2015, background): “One direction of approaches pursue high-quality motion capture in well-controlled studio setups [37, 17, 14, 38, 24].”