Gender Classification Based on Multiscale Facial Fusion Feature

Chunyu Zhang, Hui Ding, Yuanyuan Shang, Zhuhong Shao and Xiaoyan Fu

Mathematical Problems in Engineering, 2018, vol. 2018, 1-6

Abstract:

For gender classification, we present a new approach based on Multiscale facial fusion feature (MS3F) to classify gender from face images. Fusion feature is extracted by the combination of Local Binary Pattern (LBP) and Local Phase Quantization (LPQ) descriptors, and a multiscale feature is generated through Multiblock (MB) and Multilevel (ML) methods. Support Vector Machine (SVM) is employed as the classifier to conduct gender classification. All the experiments are performed based on the Images of Groups (IoG) dataset. The results demonstrate that the application of Multiscale fusion feature greatly improves the performance of gender classification, and our approach outperforms the state-of-the-art techniques.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1924151

DOI: 10.1155/2018/1924151

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