Pose Invariant People Detection in Point Clouds for Mobile Robots

Date

2019-10-28

Author

Hacınecipoğlu, Akif
Konukseven, Erhan İlhan
Koku, Ahmet Buğra

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To be able to navigate in socially complaint fashion and safely, people detection is a very important ability for robots deployed in our social environments. However, it is a challenging task since humans exhibit various poses in daily life as they bend, sit down, touch or interact with each other. A robust people detector should detect humans also in these arbitrary poses. In addition, mobile robots should be able to carry out detection in a real-time manner because our environment is highly dynamic. In this study we developed a fast head and people detector which can, pose invariantly, detect people. Method depends only on depth information of point clouds taken from RGB-D sensors. As a result, it is robust against sudden light and contrast changes. The algorithm runs relying only on CPU, which makes it applicable to mobile robots with low computational resources.

URI

http://www.icaai.org/2019.html
https://hdl.handle.net/11511/73395

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Citation Formats

A. Hacınecipoğlu, E. İ. Konukseven, and A. B. Koku, “Pose Invariant People Detection in Point Clouds for Mobile Robots,” 2019, Accessed: 00, 2021. [Online]. Available: http://www.icaai.org/2019.html.