• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Spatial-temporal texture features for 3D human activity recognition using laser-based RGB-D videos


Abstract

The IR camera and laser-based IR projector provide an effective solution for real-time collection of moving targets in RGB-D videos. Different from the traditional RGB videos, the captured depth videos are not affected by the illumination variation. In this paper, we propose a novel feature extraction framework to describe human activities based on the above optical video capturing method, namely spatial-temporal texture features for 3D human activity recognition. Spatial-temporal texture feature with depth information is insensitive to illumination and occlusions, and efficient for fine-motion description. The framework of our proposed algorithm begins with video acquisition based on laser projection, video preprocessing with visual background extraction and obtains spatial-temporal key images. Then, the texture features encoded from key images are used to generate discriminative features for human activity information. The experimental results based on the different databases and practical scenarios demonstrate the effectiveness of our proposed algorithm for the large-scale data sets.


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Cite this article

[IEEE Style]
Y. Ming, G. Wang and X. Hong, "Spatial-temporal texture features for 3D human activity recognition using laser-based RGB-D videos," KSII Transactions on Internet and Information Systems, vol. 11, no. 3, pp. 1595-1613, 2017. DOI: 10.3837/tiis.2017.03.019.

[ACM Style]
Yue Ming, Guangchao Wang, and Xiaopeng Hong. 2017. Spatial-temporal texture features for 3D human activity recognition using laser-based RGB-D videos. KSII Transactions on Internet and Information Systems, 11, 3, (2017), 1595-1613. DOI: 10.3837/tiis.2017.03.019.

[BibTeX Style]
@article{tiis:21402, title="Spatial-temporal texture features for 3D human activity recognition using laser-based RGB-D videos", author="Yue Ming and Guangchao Wang and Xiaopeng Hong and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2017.03.019}, volume={11}, number={3}, year="2017", month={March}, pages={1595-1613}}