Preliminary experiments on automatic gender recognition based on online capital letters

TL;DR

This paper explores automatic gender classification from online handwritten capital letters, achieving up to 74% accuracy, indicating potential despite handwritten text's limited discriminative power.

Contribution

It demonstrates the feasibility of gender recognition using online handwritten capital letters, a novel approach with promising accuracy.

Findings

Achieved up to 74% accuracy in gender classification.

Handwritten capital letters contain some gender-discriminative features.

Potential for gender recognition in handwritten text despite challenges.

Abstract

In this paper we present some experiments to automatically classify online handwritten text based on capital letters. Although handwritten text is not as discriminative as face or voice, we still found some chance for gender classification based on handwritten text. Accuracies are up to 74%, even in the most challenging case of capital letters.