Fast heuristic method to detect people in frontal depth images-Reference-Cited by-同舟云学术

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Fast heuristic method to detect people in frontal depth images

Published:2021-04 Issue: Volume:168 Page:114483
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Luna Carlos A.,Losada-Gutiérrez Cristina,Fuentes-Jiménez David,Mazo Manuel

Funder

Universidad de Alcalá

Ministerio de Economía y Competitividad

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference43 articles.

1. Bagautdinov, T., Fleuret, F. & Fua, P. (2015). Probability occupancy maps for occluded depth images. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 07-12-June-2015, 2829–2837. https://doi.org/10.1109/CVPR.2015.7298900.

2. Bevilacqua, A., Di Stefano, L. & Azzari, P. (2006). People Tracking Using a Time-of-Flight Depth Sensor. Video and Signal Based Surveillance, 2006. AVSS ’06. IEEE International Conference On, 89. https://doi.org/10.1109/AVSS.2006.92.

3. Beyl, T., Nicolai, P., Raczkowsky, J., Worn, H., Comparetti, M. D. & De Momi, E. (2013). Multi kinect people detection for intuitive and safe human robot cooperation in the operating room. 2013 16th International Conference on Advanced Robotics (ICAR) (pp. 1–6). https://doi.org/10.1109/ICAR.2013.6766594.

4. Da Silva Guizi, F. & Kurashima, C. S. (2016). Real-time people detection and tracking using 3D depth estimation. Proceedings of the International Symposium on Consumer Electronics, ISCE (pp. 39–40). https://doi.org/10.1109/ISCE.2016.7797359.

5. Counting people by RGB or depth overhead cameras;Del Pizzo;Pattern Recognition Letters,2016

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