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Video Surveillance Capturing, Management and Analysis of Security Videos. -Abhinav Goel -Varun Varshney

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Video Surveillance. Capturing, Management and Analysis of Security Videos. - Abhinav Goel - Varun Varshney. Introduction-why Surveillance at IIIT ?. For the implementation of all the above and more analysis schemes the biggest need of the hour is : - PowerPoint PPT Presentation

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Page 1: Video Surveillance

Video SurveillanceCapturing, Management and Analysis of Security Videos.-Abhinav Goel-Varun Varshney

Page 2: Video Surveillance

Introduction-why Surveillance at IIIT ?

Person Identification• Face Detection & Recognition

Crowd Patterns • Group Leader

Traffic Patterns/Crowd Recognition• Time when the area is crowded

Trend/Life Patterns• Hairstyle Patterns, Clothing

Patterns, Smoking habits etc.

Object Detection• Suspicious abandoned objects

Activity Detection• Coverage of Accidents,

Thefts ,vehicles arrived, rumbling crowd.

For the implementation of all the above and more analysis schemes the biggest need of the hour is : A scalable ,efficient and a robust system.

That is where we jump in !

Page 3: Video Surveillance

Video Surveillance System : Design Objectives

System Necessity:

“Design of a system for the information retrieval application on security videos.

It should act as a platform for deployment and experimentation of various video analysis algorithms(as explained earlier) on large scale.”

Robust

Modular

Scalable

?

?admin

Robust: Should be resistant to crashes.Reliable. For eg. In case of Failure : Error Reporting to admin

Scalable : More external storage devices can be easily added.

Modular: System should be divided into smaller parts so that chances of failure reduce. Layered Architecture.

Layer-1

Layer-2

Layer-3

. . .

Page 4: Video Surveillance

System Design : Modules

Continuous Camera Capture

Any camera can be installed which can be integrated with OpenCV.

The video capturing goes on continuously for 24 Hrs.

Storage DevicesVideo

Processing Station

Web ServerContinuous

Camera Capture.

Central Control

Server(CCS)

Web Server

•Hosts the interactive front end which has a user friendly interface to access the ‘Video Processing Results’.

•Sends a request a to the CCS to send the captured videos (which are temporarily stored here) to the ‘Processing Station’.

•Sends a request to CCS to search for a user requested video.

Video Processing Station

•Responsible for receiving videos from Web Server and running various Video Processing Algorithms.

•Sends a request to CCS to store the result in a suitable available storage device.

CCS

•Master Controller of the whole System.

•Accepts /Sends requests to other stations.

•Stores the meta-data corresponding to the current state of the system .(storage devices available, processing state etc.)•Stores complete meta-data of the processing results and their location.

Page 5: Video Surveillance

System Process

Continuous Incoming Frames

Segmentation Process

Further large scale Video Processing

No of white pixels=n. If there are sufficient number of boxes with total white pixels greater than a threshold => activity frame.Capturing continues till a threshold amount of 'non-activity' frames are found.

Segmentation Process

Page 6: Video Surveillance

System Process

Comparison with other techniques: It is better than Using a static image and doing background subtraction as the activity is studied at a box level.

User End:

1)A robust ,scalable system.

2) User can track all the activity videos by using a timeline.

3) A detailed census of the traffic is also available to the user along with a log of the recent activity.

4) Further features like a gallery of the  faces captured in a shot are also visible(usage of OpenCV face detector)

Page 7: Video Surveillance

System DemoSee Demo Video :(link on the website) or

Page 8: Video Surveillance

Challenges and Statistics

Stress on System Stability: Robust & Easily Scalable.

Suitable Segmentation algorithm which can particularly capture distance activity changes

User End : Easy and efficient search of Videos

Determination of suitable thresholds to distinguish between ‘active’ and ‘static’ frames. Capturing+Storage+Processing+Control

Efficient System

Test: 14 Hrs continuous capture with web camera

No system crash ,17 activity videos,2 corrupted

videos

Capturing + Processing

No Storage scalability Less stable

Start: Naive one Server Design : All on one PC

System Crashes Delay in Processing

Page 9: Video Surveillance

Technologies Used & Future Work

Front End: Mod_Python, Ajax, JavascriptDatabase : MysqlVideo Processing Tool : OpenCVProgramming Environment : Linux

This formulated system can be deployed easily at any Linux Environment with the above support.

•Installation of the external surveillance camera•Implementation of more Video Processing Algorithms to reduce Human Intervention!

-> Easy due to stable platform

Page 10: Video Surveillance

Thank You