Design and Implementation of Embedded Video Surveillance System Based on Human Detection

Jing Li; Yun Fei Bai; Jin Long He

doi:10.4028/www.scientific.net/AMM.513-517.4535

Paper Titles

Real-Time Laser Ranging System Design of High Precision and Multi-Frequency Modulation
p.4517

Research on Millimeter Wave Communication at 60GHz
p.4521

Application Study on Distributed Predictive Control of Beer Fermentation Temperature
p.4525

Automatic Matching for Frame Images of Area Remote Sensing
p.4529

Design and Implementation of Embedded Video Surveillance System Based on Human Detection
p.4535

The Researches and Applications Based on Video Statistical Analysis of Average Population Density Estimation Methods
p.4539

A Service-Oriented Spatio-Temporal Data Model of the Marine Environment
p.4543

A Safety Evaluation Method of Military Aircraft Based on Projection Pursuit Method
p.4547

A High Resolution Single Slope ADC with Low Operation Speed for Uncooled Infrared Focal Plane Array
p.4551

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517Design and Implementation of Embedded Video...

Design and Implementation of Embedded Video Surveillance System Based on Human Detection

Abstract:

In order to get information timely when elderly people fall down and need assistance, a kind of intelligent video surveillance system is designed and implemented. By using this system, the elderly dont need to wear any device. The H.264 video standard, the embedded technology, network technology, video surveillance technology and image processing technology are mixed used to detect human gesture in the video stream monitored. This system updates the background by the Gauss mixture model. The moving target is segmented by using the background subtraction algorithm. Experiments show that the system can be remote monitoring and detecting attitude. When the people falls down the system can automatically alarm, and satisfy the requirement of the timeliness, accuracy and stability.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

4535-4538

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.4535

Citation:

Cite this paper

Online since:

February 2014

Authors:

Jing Li*, Yun Fei Bai, Jin Long He

Keywords:

Embedded System, Image Processing, Intelligent Monitoring

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] ZHANG Yu. Situation and Progress of Older Fall Research[J]. Chinese Journal of Geriatric, 2008, 28(5): 929-31.

Google Scholar

[2] Shi Xin，Zhang Tao．Design of a wearable fall detection device [J]．Chinese Journal of Scientific Instrument，2012，33（3）：575-580.

Google Scholar

[3] CHEN Ying-ming, CHEN Shu-yue, ZHANG Xian-ting. Research on Abnormal Behavior Recognitionin Intelligent Surveillance[J]. Micro Electronics & Computer, 2010, 27(11): 102-105.

Google Scholar

[4] LI Wei ，XIONG Jian⁃she. Research on algorithm for human motion target detection in video images [J]. Modern Electronics Technique, 2013, 36(3): 74-77.

Google Scholar

[5] LU Hong , ZUO Chang-ling, HUANG Jiang-lin. An improved algorithm of automatic fall detection [J]. Journal of Anhui University (Natural Sciences), 2012, 36(6): 57-61.

Google Scholar