An Intelligent Alarm and Messaging Based Surveillance System for Fall Detection and Absence Recognition of Unaccompanied Child

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Author(s)

Engr Ali Javed 1,* Rabeea Islam 1

1. Department of Software Engineering, University of Engineering & Technology Taxila

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2013.03.07

Received: 14 Nov. 2012 / Revised: 13 Dec. 2012 / Accepted: 22 Jan. 2013 / Published: 8 Mar. 2013

Index Terms

Absence Recognition, Fall Detection, Surveillance

Abstract

Video analytics refers to process the videos intelligently. Video analytics has its most important usage in the field of the surveillance. Surveillance has been used in various areas and one of them is the detection of unintentional fall of patients, senior citizens and children which can cause serious injuries and health threats to children as well as to old persons. Developed countries are progressing in the Surveillance and activity monitoring. But there are limitation and facing problems under certain circumstances. Advancement in the field of computer vision and the prominent decrease in the prices of digital cameras assisted and motivated researchers to propose very useful algorithms for fall detection. The proposed research work is based on the combination of motion history images and eclipse centroid calculation to detect the fall efficiently. The proposed system provides very effective and efficient results on the video sequences of simulated falls.

Cite This Paper

Ali Javed, Rabeea Islam,"An Intelligent Alarm and Messaging Based Surveillance System for Fall Detection and Absence Recognition of Unaccompanied Child", IJIGSP, vol.5, no.3, pp.48-54, 2013. DOI: 10.5815/ijigsp.2013.03.07

Reference

[1]Zhuolin Jiang, Shaofa Li, Dongfa Gao. A Time Saving Method for Human Detection in Wide Angle Camera Images. International Conference on Machine Learning and Cyber-netics, 2006. 

[2]N. Dalal and B. Triggs. "Histograms of oriented gradients for human detection," Conference on Computer Vision and Pattern Recognition (CVPR) 2005. 

[3]Paul Viola, M Jones, ''Rapid object detection using a boosted cascade of simple features'', published in Computer Vision and pattern recognition, 2001. 

[4]Chong Chen, Schonfeld, D., "A Particle Filtering Framework for Joint Video Tracking and Pose Estimation Image Processing", IEEE Transactions, pp. 1625 – 1634, June 2010.

[5]Muhammad Jamil Khan and Hafiz Adnan Habib, "Video Analytic for Fall Detection from Shape Features and Motion Gradients", Proceedings of the World Congress on Engineering and Computer Science 2009 Vol II WCECS 2009, October 20-22, 2009, San Francisco, USA.

[6]Mohamad Adnan Al-Alaoui, Lina Al-Kanj, Jimmy Azar, Elias Yaacoub, "Speech Recognition using Artificial Neural Networks and Hidden Markov Models", IEEE Technology and Engineering Education (ITEE), Vol 3, No 3 (2008)

[7]Li Cheng; Minglun Gong; Schuurmans, D, ''Caelli, T.; Real-Time Discriminative Background Subtraction Image Processing'', IEEE Transactions, pp. 1401 – 1414, May 2011.

[8]Inter frame Coding, http://en.wikipedia.org/wiki/Inter_frame

[9]G.-X. Yuan, C.-H. Ho, and C.-J. Lin. An Improved GLMNET for L1-regularized Logistic Regression and Support Vector Machines. (supplementary materials, code). Journal of Machine Learning Research, 13(2012), 1999-2030. A short version appears at ACM KDD 2011.

[10]Bovolo, F., Bruzzone, L., Carlin, L, ''A Novel Technique for Subpixel Image Classification Based on Support Vector Machine Image Processing'', IEEE Transactions, pp. 2983 – 2999, Nov. 2010. 

[11]David G. Lowe,"Object Recognition from Local Scale-Invariant Features" Proc. of the International Conference on Computer Vision, Corfu (Sept. 1999)

[12]Nicholas, Patel, Abhishek, Fall Detection system, "http://www.ece.gatech.edu/academic/courses/ece4007/09spring/ece4007l05/ak9/"