The image based surveillance system for personnel and vehicle tracking

Chairman:Hung-Chi YangAdvisor: Yen-Ting Chen

Presenter: Fong-Ren SieDate: 2014.5.21

Outline

IntroductionPaper reviewResultsFuture WorkReferences

IntroductionThe traditional video surveillance

system◦Closed-circuit televisions (CCTV)◦Digital video recorders (DVR)

Disadvantages◦Need someone to monitor and

searchReal time intelligent video

surveillance systems◦High-cost and low-efficiency

4

IntroductionThe intelligent video surveillance

system is a convergence technology◦Detecting and tracking objects◦Analyzing their movements◦Responding

Paper review(1/2)Egocentric View Transition for

Video Monitoring in a Distributed Camera Network

(a) The original image(b) the image of virtual camera without grid-based visualization(c) the image of virtual

camera with grid-based visualization

Paper review(1/2)

(a) transition from camera 1 to camera 2, (b) transition from camera 2 to camera 3, and (c) transition from camera 3 to camera 4

Paper review(1/2)

(a) transition from camera 5 to camera 6(b) transition from camera 3 to a blind region and then back to camera 3 (c)transition from camera 3 to camera 8

Paper review(2/2)Fast and Robust Algorithm of

Tracking Multiple Moving Objects for Intelligent Video Surveillance Systems ◦Gray-scale BM

Image information is excessively attenuated.

◦RGB color model Very sensitive to even small changes

caused by light scattering or reflection.

Paper review(2/2)

Extraction of moving regions by gray-scale BM

Paper review(2/2)

The results of RGB BM according to the sensitivity parameter

Paper review(2/2)

The 152th frame

References [1] T. Bouwmans, “Recent Advanced Statistical Background

Modeling for Foreground Detection: A Systematic Survey,” Recent Patents on Computer Science, vol. 4, no. 3, pp. 147-176, 2011.

[2] T. Bouwmans, F. E. Baf, and B. Vachon, “Background Modeling using Mixture of Gaussians for Foreground Detection - A Survey,” Recent Patents on Computer Science, vol. 1, no. 3, pp. 219-237, 2008.

[3] T. Bouwmans, F. E. Baf, and B. Vachon, “Statistical Background Modeling for Foreground Detection: A Survey,” Handbook of Pattern Recognition and Computer Vision, vol. 4, no. 2, pp. 181-199, 2010.

[4]Jong Sun Kim, Dong Hae Yeom, and Young Hoon Joo, “Fast and Robust Algorithm of Tracking Multiple Moving Objects for Intelligent Video Surveillance Systems ”IEEE Transactions on Consumer Electronics, Vol. 57, No. 3, August, 2011

[5]Mukesh Kumar ,”A Real-Time Vehicle License Plate Recognition (LPR) System”,Thesis report ,THAPAR UNIVERSITY, PATIALA,INDIA,2009

Thank you for your attention