Error Compensation Heatmap Decoding for Human Pose Estimation

doi:10.1109/ACCESS.2021.3105553

Error Compensation Heatmap Decoding for Human Pose Estimation

2021-01-01

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DOI：10.1109/ACCESS.2021.3105553

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As a fundamental component of heatmap-based human pose estimation methods, heatmap decoding is to transform heatmaps into joint coordinates. We found that previous heatmap decoding methods generally ignored the effect of systematic errors introduced by the resolution increaseing operations in the network decoder. This work fills the gap by taking the systematic errors in heatmap decoding into consideration. We proposed a fast method to reduces the systematic and random errors in one shot by error compensation. The proposed method outperforms the previous best method on the COCO and the MPII datasets while being over 2 times faster. Extensive experiments with different networks, resolutions, metrics and datasets have proved the rationality of the proposed idea.

Keywords:

Heating systems

Optimized production technology

Decoding

Error compensation

Pose estimation

Systematics

Gaussian distribution

Human pose estimation

heatmap

decoding

error compensation

Error Compensation Heatmap Decoding for Human Pose Estimation

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