Estimating Anthropometry and Pose from a Single Uncalibrated Image

By Carlos Barron, Ioannis A. Kakadiaris. 2001

99 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition

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Citations in the corpus

End-to-End Recovery of Human Shape and Pose (2017, methodology): “Most methods make some assumption about the limb-length or proportions [4, 21, 32, 34].”
Reconstructing 3D Human Pose from 2D Image Landmarks (2012, methodology): “Other approaches, such as Barron and Kakadiaris [12], estimated anthropometry and pose using strong anthropometric priors on limb lengths by generating a set of plausible poses based on geometric constraints followed by a nonlinear minimization.”
Learning to Recognize Activities from the Wrong View Point (2008, background): “One alternative is to model in 3D. There is a strong evidence that 3D configuration can be inferred from 2D images (e.g., [19, 6 ,33]; see also discussion in [18]).”
Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image (2017, background): “Early approaches [19, 34, 25, 6] took advantage of anatomical knowledge of the human skeleton or joint angle limits to recover pose from a single image.”
Human Activity Recognition with Metric Learning (2008, background): “[4,5,6]; see also discussion in [7]), which suggests building appearance features for body configuration.”
Exploiting Temporal Information for 3D Human Pose Estimation (2017, methodology): “Several 3D pose methods have used this representation [30, 31, 22, 10].”
Recovering 3D human body configurations using shape contexts (2006, unknown): “Barrón and Kakadiaris [34] simultaneously estimate 3D pose and anthropometry (body parameters) from 2D joint positions in a constrained optimization method.”
A Simple Yet Effective Baseline for 3d Human Pose Estimation (2017, background): “2d to 3d angular pose There is a second branch of algorithms for inferring 3d pose from images which estimate the body configuration in terms of angles (and sometimes body shape) instead of directly estimating the 3d position of the joints [4, 7, 31, 54].”
Keep It SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image (2016, background): “Barron and Kakadiaris [7] build a statistical model of limb-length variation from extremes taken from anthropometric tables.”
Dissimilarity-based people re-identification and search for intelligent video surveillance (2013, methodology): “In [11] a method that does not require camera calibration was proposed, for simultaneously estimating anthropometric measurements and pose.”
View independent human body pose estimation from a single perspective image (2004, background): “In [1] the authors recover both anthropometry and pose of a human body.”
Pose-conditioned joint angle limits for 3D human pose reconstruction (2015, background): “Barròn and Kakadiaris [4] use joint angle limit constraints to resolve this ambiguity.”