What is it about?
Interpersonal and intrapersonal face variation interference caused by multiple poses is challenging for distance-based face recognition systems.
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Photo by Google DeepMind on Unsplash
Why is it important?
In this paper, we investigate the face-feature distance distribution for Chinese multi-pose faces.
Perspectives
The simulation shows that the number of individuals in the gallery database will greatly affect the recognition performance for near-profile face images. It also provides a prediction of the Top-N occurrence rates in different gallery-size environments.
Richard (Ricky) Smith Jr.
Read the Original
This page is a summary of: A Study of Multi-Pose Effects On a Face Recognition System, IgMin Research, July 2024, IgMin Publications Inc.,
DOI: 10.61927/igmin231.
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