An online background subtraction algorithm deployed on a NAO humanoid robot based monitoring system

Hu, Yang and Sirlantzis, Konstantinos and Howells, Gareth and Ragot, Nicolas and Rodriguez, Paul (2016) An online background subtraction algorithm deployed on a NAO humanoid robot based monitoring system. Robotics and Autonomous Systems, 85 . pp. 37-47. ISSN 0921-8890. (doi:https://doi.org/10.1016/j.robot.2016.08.013) (Full text available)

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Abstract

In this paper, we design a fast background subtraction algorithm and deploy this algorithm on a monitoring system based on NAO humanoid robot. The proposed algorithm detects a contiguous foreground via a contiguously weighted linear regression (CWLR) model. It consists of a background model and a foreground model. The background model is a regression based low rank model. It seeks a low rank background subspace and represents the background as the linear combination of the basis spanning the subspace. The foreground model promotes the contiguity in the foreground detection. It encourages the foreground to be detected as whole regions rather than separated pixels. We formulate the background and foreground model into a contiguously weighted linear regression problem. This problem can be solved efficiently via an alternating optimization approach which includes continuous and discrete variables. Given an image sequence, we use the first few frames to incrementally initialize the background subspace, and we determine the background and foreground in the following frames in an online scheme using the proposed CWLR model, with the background subspace continuously updated using the detected background information. The proposed algorithm is implemented by Python on a NAO humanoid robot based monitoring system. This system consists of a control station and a Nao robot. The Nao robot acts as a mobile probe. It captures image sequence and sends it to the control station. The control station serves as a control terminal. It sends commands to control the behaviour of Nao robot, and it processes the image data sent by Nao. This system can be used for living environment monitoring and form the basis for many vision-based applications like fall detection and scene understanding. The experimental comparisons with most recent algorithms on both benchmark dataset and NAO captures demonstrate the high effectiveness of the proposed algorithm.

Item Type: Article
Uncontrolled keywords: background subtraction, contiguity, NAO humanoid robot, monitoring system
Subjects: T Technology > TJ Mechanical engineering and machinery > Intelligent control systems
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Konstantinos Sirlantzis
Date Deposited: 14 Dec 2015 02:42 UTC
Last Modified: 01 Sep 2017 23:00 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/53323 (The current URI for this page, for reference purposes)
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