A framework for analysis and synthesis of human gait patterns

By N. Troje. 2002

1,124 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9eda2d217dcd279fa97625845c9c34ab7f75b4aa

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Citations in the corpus

Fuzzy human motion analysis: A review (2014, background): “For decades, it has been a popular research topic that crossovers many domains such as biology [1,2], psychology [3,4], multimedia [5] and so on.”
Low-dimensional models and performance scaling of a highly deformable fish pectoral fin (2009, unknown): “Representing motions as linear sums of principal components has become a widely accepted animation technique (Alexa & Mueller 2000; Troje 2000).”
MotionBERT: A Unified Perspective on Learning Human Motion Representations (2022, methodology): “AMASS [71] integrates most existing marker-based Mocap datasets [1,2,4,10,14,17,32,35,48,65,67,72,79,90,103,104] and parameterizes them with a common representation.”
A Study on Gait-Based Gender Classification (2009, background): “The CCR is 69% and within the range of the results in [5], [8].”
On Human Motion Prediction Using Recurrent Neural Networks (2017, background): “wide variety of fields, such as action prediction for sociallyaware robotics [21], 3D people tracking within computer vision [13,43], motion generation for computer graphics [22] or modeling biological motion in psychology [42].”
Bayesian models of object perception. (2003, background): “They constrain local boundary detection (Figure 3a; [21 ]), identify regularities on the changes of image features as illumination conditions vary (Figure 3b; [22]), and help to interpret human body motion [23].”
DLow: Diversifying Latent Flows for Diverse Human Motion Prediction (2020, background): “Human motion prediction, i.e., predicting the future 3D poses of a person based on past poses, is an important problem in computer vision and has many useful applications in autonomous driving [55], human robot interaction [39] and healthcare [67].”
Short-term mating strategies and attraction to masculinity in point-light walkers (2008, unknown): “Keywords: Sociosexuality; Fertility status; Immunocompetence; Biological motion; Masculinity”
Human Action Recognition and Prediction: A Survey (2018, background): “There are a number of information we can tell from human actions, including the action categories [62], emotional implication [63], identity [64], [65], gender [66], [67], etc.”
Nonrigid Structure-from-Motion: Estimating Shape and Motion with Hierarchical Priors (2008, methodology): “We first suggest restricting shapes to lie within a lowdimensional subspace, and describe estimation algorithms.”
AMASS: Archive of Motion Capture As Surface Shapes (2019, methodology): “A sampling of shapes and poses from a few datasets in AMASS is shown, from left to right: CMU [9], MPI-HDM05 [30, 31], MPIPose Limits [3], KIT [27], BMLrub [42], TCD [21] and ACCAD [34] datasets.”
What is biological motion?: Definition, stimuli and paradigms (2012, background): “…the point-light displays to investigate the role of motion-mediated structure, on the one hand, and the kinematics of the body, on the other hand (Mather and Murdoch, 1994; Troje, 2002; Troje, Westhoff, and Lavrov, 2005; Westhoff and Troje, 2007) for gender classification and person identification.”
Perception of human motion. (2007, methodology): “Observers also readily perceive the identity (Cutting & Kozlowski 1977, Fani et al. 2005, Troje et al. 2005) and sex (Kozlowski & Cutting 1977, 1978; Mather & Murdoch 1994; Sumi 2000; Troje 2002) of a PL-defined walker, although recognition performance is not perfect (Pollick et al. 2005).”
Self-organizing neural integration of pose-motion features for human action recognition (2015, background): “…there has been a long-standing debate on which visual cue was predominant to action coding, i.e., either posture (Lange et al., 2006) or motion (Troje, 2002), additional studies have found neurons in the macaque superior temporal sulcus (STS) that are sensitive to both motion and posture for…”