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Human detection and tracking in an assistive living service robot through multimodal data fusion

Noyvirt, Alexandre Emilov and Qiu, Renxi 2012. Human detection and tracking in an assistive living service robot through multimodal data fusion. Presented at: 10th IEEE International Conference on Industrial Informatics (INDIN), 2012, Beijing, China, 25-27 July 2012. INDIN 2012: IEEE 10th International Conference on Industrial Informatics. Los Alamitos, CA: IEEE, pp. 1176-1181. 10.1109/INDIN.2012.6301153

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Abstract

A new method is proposed for using a combination of measurements from a laser range finder and a depth camera in a data fusion process that benefits from each modality's strong side. The combination leads to a significantly improved performance of the human detection and tracking in comparison with what is achievable from the singular modalities. The useful information from both laser and depth camera is automatically extracted and combined in a Bayesian formulation that is estimated using a Markov Chain Monte Carlo (MCMC) sampling framework. The experiments show that this algorithm can track robustly multiple people in real world assistive robotics applications.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Engineering
Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TA Engineering (General). Civil engineering (General)
Uncontrolled Keywords: MCMC, assistive technology, human detection, human tracking, sensor data fusion, service robotics
Publisher: IEEE
ISBN: 9781467303118
Last Modified: 29 Apr 2016 02:59
URI: http://orca.cf.ac.uk/id/eprint/38345

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