HUMAN MOTION DETECTION AND TRACKING FOR

VEDIO SURVEILLANCE

PREPARED BY NEHA

THADEUSS5 CT

41

DOMAIN INTRODUCTIONWHAT IS IMAGE PROCESSING?

Image processing is any form of signal processing .

WHAT IS VCA? It is the capability of automatically analyzing the video.

WHAT IS THIS METHOD?An approach to detect and track

groups of people and to automatically recognize their behavior.

This method keeps track of individuals moving together by maintaining a

spacial and temporal group coherence .

THE WORKINGFirstly the people are individually

detected and tracked

Secondly their trajectories are analyzed over a temporal window

and clustered using Mean-Shift Algorithm.

EXISISTING SYSTEMThey are in three categories: the

pattern recognition models, the state based models and semantic models.

First is based on artificial vision.Second is based on reusing of

metadata.Finally the collaborative effects of

human can lead to data.

SYSTEM REQUIREMENTS1.HARDWARE SYSTEM

CONFIGURATIONProcessor=Pentium-iv.Speed=1.1Ghz.RAM=512MB.Hard disk=40GB.Keyboard=standard windows keyboard.Mouse=two or three button mouse.Monitor=normal monitor.

2. SOFTWARE SYSTEM CONFIGURATION

Operating system=windows XP7/8.

Framework=Visual Studio 2008.

Frontend=C#.net.

MODULES DESCRIPTION 1. VIDEO FILE•Video file is the input.•Then detect human activity.

2. Foreground blobs description

•Blobs of foreground pixels are grouped to form physical objects classified into predefined categories based on 3-D size of objects .•When people overlap or are close to each other, segmentation fails to split them and is treated as a single object as group of persons.•Those classes of objects are specified using Gaussian functions.

3.PHYSICAL OBJECT TRACKING•Video sequences are abstract in physical objects.•Then these objects are used to recognize events.4.GROUP TRACKING•It is based on people detection.•For group behavior recognition ,detected group objects within the video sequence and scene context objects are described.•It helps to reconagnize specific events.

5. EVENT DETECTION•Event recognition is a key task.• A typical detection algorithm takes input as a video sequence and extract interesting objects and these objects are used to model objects.•Finally the events are recognized and the abstraction stage determines which modeling technique is applied.•The output of the group tracker is a set of tracked groups having properties.

CONCLUSIONThis approach gives satisfying results

even on very challenging datasets.

The vision primitives are based on global attributes of groups.

It has a limitation for some specific events like.

FUTURE ENHANCEMENT

The primary aim of this research is to develop for an automatic semantic content extraction system which can be utilized in various areas.