Percentage of correct keypoints (PCK)

Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

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4 citations of this metric

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PCK is used as an accuracy metric that measures if the predicted keypoint and the true joint are within a certain distance threshold. The PCK is usually set with respect to the scale of the subject, which is enclosed within the bounding box. The threshold can either be:

- PCKh@0.5 is when the threshold = 50% of the head bone link
- PCK@0.2 = Distance between predicted and true joint < 0.2 * torso diameter
- Sometimes 150 mm is taken as the threshold.
- It alleviates the shorter limb problem since shorter limbs have smaller torsos and head bone links.
- PCK is used for 2D and 3D (PCK3D)

About the metric

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Objective(s):

Robustness

Purpose(s):

Event/anomaly detection
Forecasting/prediction
Recognition/object detection

Lifecycle stage(s):

Verify & validate
Build & interpret model

Target users:

Developer

Risk management stage(s):

Define
Assess

Github stars:

7100

Github forks:

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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.