Structured Aleatoric Uncertainty in Human Pose Estimation

Nitesh B. Gundavarapu, Divyansh Srivastava, Rahul Mitra, Abhishek Sharma, Arjun Jain; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019, pp. 50-53

Abstract


Human pose estimation from monocular images exhibits an inherent uncertainty through self-occlusions and inter-person occlusions, aside from typical sources of uncertainty. Recently, there has been an increased focus in modelling uncertainty in supervised machine learning tasks. In line with this trend, we propose a novel formulation to capture aleatoric uncertainty in human pose using a multivariate Gaussian distribution over all the joints of human body and show that this improves generalization in 2D hu- man pose estimation by implicitly suppressing the gradients from uncertain joints. Further, we develop a novel method to triangulate 3D human pose from predicted 2D poses, under the predicted uncertainty, that out-performs the baselines by over 10.8% and provide a multi-view inference benchmark for 3D human pose estimation on Human 3.6M dataset.

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[bibtex]
@InProceedings{Gundavarapu_2019_CVPR_Workshops,
author = {Gundavarapu, Nitesh B. and Srivastava, Divyansh and Mitra, Rahul and Sharma, Abhishek and Jain, Arjun},
title = {Structured Aleatoric Uncertainty in Human Pose Estimation},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}