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The visitor that is under consideration or intended to be tracked.
The organization such as bank, departmental store shopping mall etc. where the VISS is implemented.
The person that operates VISS.
DEVELOPMENT OF VISUAL INFORMATION SYSTEM FOR PERVASIVE SURVEILLANCE
Under Supervision of
Dr. Adnan Ashraf
Group ID 16
Hira Gul (11CS74)
Isbah Kiran (11CS68)
Farwa Siddiqui (11CS152)
Riaz Ahmed (11CS48)
Madeeha Shaikh (11CS32)
• Problem Statement
• Aims And Objectives
• Related Work
• Proposed Visual Information System
• Design & Development Of VISS
• Working Analysis of VISS
Surveillance is an important tool to fight against Terrorism
Basic security need is to install CCTV cameras in the Premises of
Extraction of concern information from bulk of CCTV footage is laborious and time taking.
Separate systems are deployed for performance evaluation and security.
To propose a pro-active system that helps in performance evaluation and automates the investigation process.
To track, monitor and report an on-demand visual history of any detected identity through facial recognition.
AIMS AND OBJECTIVES
Face recognition system by Hitachi
SYSTEM FOR PERVASIVE SURVEILLANCE
FEATURES OF VISS
Evaluating performance in terms of time spent by target
Evaluating number of visitors per day
Tracking Target through all CCTV cameras in focused area
DESIGN AND DEVELOPMENT
Agile development model
USE CASE DIAGRAM
Face Detection: ViolaJones
Generation Of Report
CONFIGURATION OF VISS
Successfully developed an application i.e. Visual Information System for pervasive Surveillance.
It is an application which is tailored to meet the requirement of proactive security system.
Thus, with VISS the various surveillance challenges to bank branches including security systems can be overcome.
i. Tracking multiple faces at a time.
ii. Making tracking of face possible under insufficient luminosity conditions as well.
iii. Adding filters which eliminates some objects falsely detected as face.
iv. Practical implementation of performance evaluation feature.
 Michael Grubinger, Content-based image indexing and retrieval for visual information systems. FTS THESIS 005.74 SO 30001006981692 So. uing Wah Simon, 2007.
 What is agile model – advantages, disadvantages and when to use it?. (2010, January 1). Retrieved from http://istqbexamcertification.com/what-is-agile-model-advantages-disadvantages-and-when-to-use-it/.
 Author, Mustafa Sayeed. (27/07/2012). Face detection using MATLAB. Retrieved from http://engineeringprojects101.blogspot.com/2012/07/face-detection-using-matlab.html.
 Face Detection and Tracking Using KLT. (n.d.). Retrieved from http://www.mathworks.com/help/vision/examples/face-detection-and-tracking-using-the-klt-algorithm.html
 Face Detection and Tracking Using CAMshift. (n.d.). Retrieved from http://www.mathworks.com/help/vision/examples/face-detection-and-tracking-using-camshift.html.
 Eric Limer. (2012, March 23). Japanese Surveillance system can scan 36 million faces in a second. Retrieved from http://www.themarysue.com/system-scans-36-mil-faces/.
Figure 1 an illustration showing evaluation of turn around time
Figure 2 an illustration showing evaluation of number of visitors
Figure 3 an illustration Extraction of target's recording
Figure 5 a use case diagram of VISS
Figure 6 activity diagram of VISS
Figure 7 Sequence diagram of VISS
Figure 4 an illustration showing steps of agile development model
Table 1 hardware & software requirements of VISS
Table 2 Comparison between VISS & Face Recognition System by Hitachi