Gait-based age estimation using a whole-generation gait database
Gait-based age estimation using a whole-generation gait database
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DOI：
10.1109/ijcb.2011.6117531
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发表时间：
2011-10
期刊：
影响因子：
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通讯作者：
Yasushi Makihara;Mayu Okumura;Haruyuki Iwama;Y. Yagi
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文献类型：
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作者：
Yasushi Makihara;Mayu Okumura;Haruyuki Iwama;Y. Yagi
本文使用大规模全代步态数据库解决基于步态的年龄估计。之前基于步态的年龄估计的工作使用的数据库评估了他们的方法，该数据库最多只包含 170 名受试者，年龄变化有限，这不足以从统计上证明基于步态的年龄估计的可能性。因此，我们首先构建了一个更大的全代步态数据库，其中包括 1,728 名年龄从 2 岁到 94 岁的受试者。然后，我们提供了一种通过高斯过程回归实现的基于步态的年龄估计的基线算法，该算法在基于人脸的年龄估计领域取得了成功，结合基于轮廓的步态特征，例如已广泛用于许多步态识别算法的平均轮廓（或步态能量图像）。最后，使用全代步态数据库的实验证明了基于步态的年龄估计的可行性。
This paper addresses gait-based age estimation using a large-scale whole-generation gait database. Previous work on gait-based age estimation evaluated their methods using databases that included only 170 subjects at most with a limited age variation, which was insufficient to statistically demonstrate the possibility of gait-based age estimation. Therefore, we first constructed a much larger whole-generation gait database which includes 1,728 subjects with ages ranging from 2 to 94 years. We then provided a baseline algorithm for gait-based age estimation implemented by Gaussian process regression, which has achieved successes in the face-based age estimation field, in conjunction with silhouette-based gait features such as an averaged silhouette (or Gait Energy Image) which has been used extensively in many gait recognition algorithms. Finally, experiments using the whole-generation gait database demonstrated the viability of gait-based age estimation.