DeepPose: Human Pose Estimation via Deep Neural Networks

We propose a method for human pose estimation based on Deep Neural Networks (DNNs). The pose estimation is formulated as a DNN-based regression problem towards body joints. We present a cascade of such DNN regres- sors which results in high precision pose estimates. The approach has the advantage of...

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Bibliographic Details
Published in2014 IEEE Conference on Computer Vision and Pattern Recognition pp. 1653 - 1660
Main Authors Toshev, Alexander, Szegedy, Christian
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 01.06.2014
Subjects
Benchmarks
cascades
Computational modeling
Computer vision
Conferences
deep learning
Detectors
Estimates
Estimation
Human
human pose estimation
Joints
Measurement
Neural networks
Pattern recognition
Regression
Titanium dioxide
Training
Vectors
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Summary:We propose a method for human pose estimation based on Deep Neural Networks (DNNs). The pose estimation is formulated as a DNN-based regression problem towards body joints. We present a cascade of such DNN regres- sors which results in high precision pose estimates. The approach has the advantage of reasoning about pose in a holistic fashion and has a simple but yet powerful formula- tion which capitalizes on recent advances in Deep Learn- ing. We present a detailed empirical analysis with state-of- art or better performance on four academic benchmarks of diverse real-world images.
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ISSN:1063-6919
1063-6919
2575-7075
DOI:10.1109/CVPR.2014.214