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Updated: Dec 17, 2025

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research

Published on: June 7, 2024

Image-Based Somatotype as a Biometric Trait for Non-Collaborative Person Recognition at a Distance and On-The-Move.

Antonios Danelakis¹, Theoharis Theoharis¹

¹Department of Computer Science, Norwegian University of Science and Technology, 7030 Trondheim, Norway.

Sensors (Basel, Switzerland)

|June 21, 2020

Summary

This summary is machine-generated.

Somatotype, derived from full-body images, is a novel soft biometric for distant person recognition. This method is effective for identification and verification, even for non-collaborative individuals.

Keywords:

biometrics deep learning full body image fusion scheme inception V3 network siamese network somatotype as biometric somatotype trait

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Area of Science:

Computer Science
Biometrics
Artificial Intelligence

Background:

Full-body images reveal somatotype, a biometric trait persistent despite apparel changes.
Somatotype can be captured easily from a distance using standard 2D cameras.

Purpose of the Study:

Investigate full-body image-based somatotype as a novel soft biometric feature.
Evaluate somatotype for person recognition at a distance and on-the-move.
Assess its utility in identification and verification scenarios.

Main Methods:

Utilized two distinct deep networks for identification and verification tasks.
Conducted experiments on popular, publicly available datasets.
Focused on person recognition using somatotype as a soft biometric.

Main Results:

Somatotype is a valuable biometric trait for identity recognition at a distance and on-the-move.
The ease of image acquisition makes it suitable for non-collaborative individuals.
Demonstrated effectiveness in both identification and verification scenarios.

Conclusions:

Somatotype-based person recognition is feasible and effective for non-collaborative scenarios.
This soft biometric trait offers advantages for distant and on-the-move recognition.
Somatotype shows potential for integration into broader biometric fusion schemes.