Human Pose Estimation and Activity Classification Using Machine Learning Approach-Reference-Cited by-同舟云学术

Human Pose Estimation and Activity Classification Using Machine Learning Approach

Published:2020 Issue: Volume: Page:113-123
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Arunnehru J.,Nandhana Davi A. K.,Sharan R. Raghul,Nambiar Poornima G.

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-2475-2_11

Reference19 articles.

1. Lin, Y.C., Hu, M.C., Cheng, W.H., Hsieh, Y.H., Chen, H.M.: Human action recognition and retrieval using sole depth information. In: Proceedings of the 20th ACM International Conference on Multimedia, pp. 1053–1056

2. Wang, J., Liu, Z., Wu, Y., Yuan, J.: Mining actionlet ensemble for action recognition with depth cameras. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1290–1297 (2012)

3. Arunnehru, J., Geetha, M.K.: Internet of things based intelligent elderly care system. Internet Things: Nov. Adv. Envisioned Appli. 207–229 (2017)

4. Ni, B., Wang, G., Moulin, P.: A color-depth video database for human daily activity recognition. IEEE international conference on computer vision workshops (ICCV workshops), vol. 2011, pp. 1147–1153 (2017)

5. Megavannan, V., Agarwal, B., Babu, R.V.: Human action recognition using depth maps. In: International Conference on Signal Processing and Communications (SPCOM), vol. 2012, pp. 1–5 (2012)

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