24-Abstract by kishorkna


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									                Real-Time Moving Object Tracking

The use of video is becoming prevalent in many applications such as monitoring of traffic,
detection of pedestrians,identification of anomalous behaviour in a parking lot or near an ATM,
etc. While a single image provides a snap of scene, the different frames of a video taken over
time reprents the dynamics in the scene,making it possible to capture motion in the sequence.

       In this project the real time tracking system, which detect an object entering the field of
view of a camera and execute tracking of the detected object. In this, we allow the model of the
target to vary dynamically during the tracking process so that it can assimilate varatiations of
shape and intensities of the target object. The tracking history can then be encoded into state
parameters of kalman filter.

        A stationary background is taken as reference image. Then every frame is compared
with this image. If the number of pixels whose grey-level differs significantly from the reference
image, then we can confirm that there is an object entering. This algorithm is Inter-frame
differentiation algorithm.

        The goal of our design is real time tracking with fairly good accuracy. More over since
the algorithm is very efficient, we can process almost every frame in real time, amounting to a
processing rate of 30 frames per second. This enables correct detection and tracking of very
rapid moving object.

Hardware and software requirements for the project:

Hardware: web cam

Software: Matlab 7.0.4 software

                                 Web camera

                                Frame gabber

                     Reference frame       Current frame

                              Detecting module

                                           Yes. object enters.
                                  Initial model

                               Tracking module

                               Kalman      filter
                                 Kalman filter

Students:                                              Guide: Ms.Thripurna
                               Kalman filter

2.Bhagyasree B (07245A0403)    Kalmer filter
3.Swathi priyanka(07245A404)

4.Bhargavi S (07245A408)

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