The document discusses object detection and tracking, emphasizing its importance in computer vision, particularly for video surveillance applications. It explores the challenges of tracking moving objects due to camera motion and proposes advanced algorithms, such as a feature-guided filter using Markov Chain Monte Carlo, to improve accuracy. Additionally, it addresses the need for a secure surveillance system to reduce crime through effective monitoring without the high costs associated with traditional methods.

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5. Introduction:
Object detection and tracking is the problem of finding the motion
of an object in an image sequence. It is result for:
 Animation & Interaction
 Navigation
 Recognition of objects
 Video surveillance
 Medical applications
 Computer assisted living
There is no doubt that moving object and detection and tracking
is one of the very important topics in the field of computer vision
research.
Video tracking is the process of locating a moving object (or
multiple objects) over time using a camera. It has a variety of
uses, some of which are: human-computer interaction, security
and surveillance, video communication and compression,
augmented reality, traffic control, medical imaging and video
editing. Video tracking can be a time consuming process due to
the amount of data that is contained in video. Adding further to
the complexity is the possible need to use object recognition
techniques for tracking, a challenging problem in its own right.
We typically distinguish 3 cases:
Tracking rigid objects
Tracking articulated objects like humans or animals.
Tracking fully non-rigid objects.

6. Classical Moving object detection and tracking methods for the
steady cameras are inadequate for the moving ones because there
are some Differences in the assumptions of each one. The field of
computer vision includes very important topics, one of them is
object detection and tracking especially moving objects, after
many years of search in working on steady cameras, it was
necessary to develop some sophisticated algorithms in the field
of object detection and tracking and it will be mentioned later
with further clarification.
In this paper it is applied on video surveillance but it should be
known that it can be applied on some different topics like: driving
safety assistance, robot navigation, and content based video
coding.
It must be known well that moving object detection and tracking
is the basic step towards the further analysis of the image
sequences in video surveillance.
The ability of moving object detection and tracking can naturally
improve the driving safety for robot.
There are some particle filters can work well for steady cameras
but they are not well for moving ones.
Moving cameras have some sudden movements and shakings that
can lead to image blur and Noticeable change in the size and
positions which will result in the tracking failure so some new
algorithms had developed to overcome the problem of tracking
failure result from the sudden movements and they can track
moving objects with its original position and sizes.
There is a filter called feature-guided it is derived for tracking
moving objects, by a technique called Markov chain Monte
Carlo (MCMC) the mentioned filter could be implemented
efficiently.
This paper is completely or partially related to the fields:
computer vision and image processing. Machine learning and

7. pattern recognition techniques will be integrated for developing
new algorithms for object detection and tracking to improve the
last results and it is the target.
As we mentioned previously our goal is to apply the methods and
tools in with different types of cameras, so we just need to the
information of the image.
Here are some advantages perhaps the most notable is that we do
not need information coming from lasers, radars, odometers and
GPSs. Other one is that our methods do not need to camera
calibration and prior training.
These methods have been used previously and showed that it is
possible to detect and track objects without the need for some
restrictions.
So let's agree that our project is divided into two parts .the first
one is to recognize the moving object of interest and then to track
these moving objects through its motion.
Pay attention, some problems may face your two parts. One of
them that can face the first part is noise:
You do not know the reason of some moving pixels in the image
if it is due to the moving of the camera or the noisy of the
background that are not of interest. So we think the solution for
this problem is that we will use size constraint to give up the
unimportant parts that will be too small to be part of the object of
interest.
We came to the second problem that can face the second part and
it is how to correctly identify the objects of interest in all the
image frames.
Using motion detection alone to track the targets provides a poor
method due to the noisy movements.
Template matching alone is not robust against change in object
orientation and tends to drift off when targets are in motion.

8. Hence, we use a combination of the two by performing template
matching only on the pixels that are moving. Results have shown
this to be a robust method in both recognizing the objects as well
as tracking them.
Problem statement:
Firstly, let's differentiate between different concepts, but both are
inseparable complements the other. What the difference between
detecting objects and tracking objects??? There is a big difference
between the two concepts as the first means to find the instance
which will be face, cars, bike, building in image and video or any
other instance. So the logical and next step of detecting is
tracking. Simply tracking means monitoring the object motion
and all changes in video sequence including its presence,
position, size and shape. So logically tracking starts with
detecting objects. While detecting an object repeatedly in
subsequent image sequence is often necessary to help and verify
tracking.
Our problem lies in determining the basic objects as it crossed in
front of the cameras and then trace these objects to get to the last
point it stands then take the necessary attitude and this is the focus
of our conversation in the following pages.
Firstly it will be located next to the cameras warning system, the
cameras will work as an observer in a normal and natural, but
when it sees something strange the alarm device will work to
warn one of the employees to monitor the site being monitored to
see What detection alarm whether a human being or otherwise .if
it was a human being be dealt with according to the regulations,
considering that this case of theft or trespass on the property,
whether private property or public, and if it is, for example,
crossing the object but not , the alarm normally and naturally
works but does not consider the case of encroachment on the
property. As the signal system worked in this case it is make sure

9. the quality of the system and that the device works even with the
crossing of living things is the human in front of the cameras.
Our real problem is to prevent crime not cure it according to the
sentence which say "prevention is better than cure" we want to
use technology to reduce the number of crimes in our society
aiming to Harness all means of science to limit committing fewer
crimes.
Why not we have all possible ways to do that although they may
be very hard for achieving.
There is no doubt Crimes are varied in the world from theft to
murder and other types. The motives are varied so also between
hunger and poverty, and sometimes for greed and perhaps to
terrorize citizens in the last while.
All organizations calling for peace in the world calls for reducing
crime, whether by educating citizen's seriousness or taking the
necessary precautions to reduce them gradually until they are
disposed of once and for all. It had to be the presence of
technology, mainly as the largest contributors for solving such a
problem, at least in a narrow between private places and public
ones enclosed scale down to the streets until it was difficult to
achieve at the moment.
Technology and scientific progress Facilitated the reduction of
crime largely by invention of such systems that are monitoring
places of interest and private places of citizens as it by informing
citizens that all of these places are under control and this is their
right, we do so to avoid the occurrence of the crime from the
ground up rather than occurrence then processed.
As we mentioned previously, the solution of this problem is
developing a secure system can monitor any vital place all the day
all the week so we need large servers to record all these videos
So we need high quality storage devices for the storage of such
bulky videos and then discharged if we did not need it, and here

10. the cost may come, but as part of the solution we can use cloud
computing and renting storage certain as we need and discharge
it from time to time to store the other as the price of renting these
servers will not It is costly to the point of not afford. It has also
given the benefits of and behind the use of a secure electronic
system by comparing the old traditional system is probably not
the price expensive. Instead of hiring more security persons we
may underestimate the cost with the existence of this security
system. This system must have the highest provider and the latest
means of safety and protection so as not to breach. We hope here
that the system will perform all the functions desired from. This
system will be subject to the experience over and over again until
we reach the best results and trying to reduce the percent of the
mistake until we can remove it completely.
Contributions:
Avery important benefit behind our project is reducing time,
effort and money. In traditional surveillance systems the one
place should be guarded by more than one persons. The percent
of mistake from these persons may be high, the quality may be
weak, the cost may be very high and finally Possibility of a crime
may be high.
Our system of surveillance cameras 24 hours a day, as we
mentioned provider with high-quality warning is working
safely, effectively and efficiently to the greatest degree
possible. it also is not required to remain in front of the
cameras monitoring throughout the specified period , of
course, leads to some extent to waste time and effort.
Therefore, it is possible to leave the cameras and perform
another task at the same time and the alarm will notify you
with anything strange going to happen according to the
programming device. It is also possible to use the system

11. device for recording in the absence of human guard and
when you get back, instead of wasting time and effort in
the video review of the Register and may be the
registration period very large and our system gives you the
ample opportunity to review only critical moments that
something may have happened to them from theft or
anything non grata, where it recorded these moments and
it will immediately notify you by your return.
It should be well known that the ultimate objective behind
this system is to fine tune the citizens and automatically
prevent them from committing crimes. So protecting man
even from himself must be the goal of every person until
a higher status in a moral refrain people spontaneously
from committing crimes.

12. Here is a very simple block diagram for our system.