The OU-ISIR gait database comprising the treadmill dataset

被引：141

作者：

Makihara, Yasushi ^{[1
]}

Mannami, Hidetoshi ^{[1
]}

Tsuji, Akira ^{[1
]}

Hossain, Md. Altab ^{[1
,2
]}

Sugiura, Kazushige ^{[1
]}

Mori, Atsushi ^{[1
]}

Yagi, Yasushi ^{[1
]}

机构：

[1] Osaka University, Ibaraki

[2] University of Rajshahi, Rajshahi

来源：

IPSJ Transactions on Computer Vision and Applications | 2012年 / 4卷

关键词：

Clothing; Gait database; Multiple views; Treadmill; Walking speed;

D O I：

10.2197/ipsjtcva.4.53

中图分类号：

学科分类号：

摘要：

This paper describes a large-scale gait database comprising the Treadmill Dataset. The dataset focuses on variations in walking conditions and includes 200 subjects with 25 views, 34 subjects with 9 speed variations from 2km/h to 10km/h with a 1km/h interval, and 68 subjects with at most 32 clothes variations. The range of variations in these three factors is significantly larger than that of previous gait databases, and therefore, the Treadmill Dataset can be used in research on invariant gait recognition. Moreover, the dataset contains more diverse gender and ages than the existing databases and hence it enables us to evaluate gait-based gender and age group classification in more statistically reliable way. © 2012 Information Processing Society of Japan.

引用

页码：53 / 62

页数：9

共 45 条

[1]

Aqmar M.R., Shinoda K., Furui S., Robust gait recognition against speed variation, Proc. 20th Int. Conf. on Pattern Recognition, pp. 2190-2193, (2010)

[2]

Begg R., Support vector machines for automated gait classification, IEEE Trans. Biomedical Engineering, 52, 5, pp. 828-838, (2005)

[3]

Benabdelkader C., Culter R., Nanda H., Davis L., Eigengait: Motion-based recognition people using image self-similarity, Proc. Int. Conf. on Audio and Video-based Person Authentication, pp. 284-294, (2001)

[4]

Bobick A., Johnson A., Gait recognition using static activityspecific parameters, Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 1, pp. 423-430, (2001)

[5]

Bouchrika I., Nixon M., Exploratory factor analysis of gait recognition, 8th IEEE International Conference on Automatic Face and Gesture Recognition, (2008)

[6]

Cuntoor N., Kale A., Chellappa R., Combining multiple evidences for gait recognition, Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, 3, pp. 33-36, (2003)

[7]

Gross R., Shi J., The CMU Motion of Body (MoBo) Database, (2001)

[8]

Han J., Bhanu B., Individual recognition using gait energy image, Trans. Pattern Analysis and Machine Intelligence, 28, 2, pp. 316-322, (2006)

[9]

Hossain M.A., Makihara Y., Wang J., Yagi Y., Clothing-invariant gait identification using part-based clothing categorization and adaptive weight control, Pattern Recognition, 43, 6, pp. 2281-2291, (2010)

[10]

Kobayashi T., Otsu N., Action and simultaneous multiple-person identification using cubic higher-order local auto-correlation, Proc. 17th Int. Conf. on Pattern Recognition, 3, pp. 741-744, (2004)

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