Component Biologically Inspired Features With Moving Segmentation for Age Estimation

Gee-Sern Jison Hsu, Yi-Tseng Cheng, Choon Ching Ng, Moi Hoon Yap; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2017, pp. 38-45

Abstract


We propose the Component Bio-Inspired Feature (CBIF) with a moving segmentation scheme for age estimation. The CBIF defines a superset for the commonly used Bio-Inspired Feature (BIF) with more parameters and flexibility in settings, resulting in features with abundant characteristics. An in-depth study is performed for the determination of the parameters good for capturing age-related traits. The moving segmentation is proposed to better determine the age boundaries good for age grouping, and improve the overall performance. The proposed approach is evaluated on two common benchmarks, FG-NET and MORPH databases, and compared with contemporary approaches to demonstrate its efficacy.

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[bibtex]
@InProceedings{Hsu_2017_CVPR_Workshops,
author = {Jison Hsu, Gee-Sern and Cheng, Yi-Tseng and Ching Ng, Choon and Hoon Yap, Moi},
title = {Component Biologically Inspired Features With Moving Segmentation for Age Estimation},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {July},
year = {2017}
}