In and locations of the captured objects belonging

In modern life, we see many
challenges and problems associated with the buildup of technology. Multi-object
tracking is non-different from this. Ever since the terrorist attack that
happened in New York people wanted better security. Indeed, the surveillance
cameras to provide the efficient
security, but there is a need to make it better by decoding its algorithms. They
desired these cameras to focus on detecting humans with suspicion more
accurately.

 

There is a need to have high-quality methods for getting the better
accuracy at targeting wrongdoings. People
have developed and proposed multiple ways for this but that was not efficient.
Till now cameras are capturing only one single target.

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People then proposed the idea of
having a multi-camera system to capture the
actions of one single person. For this, they will need different kinds of
algorithms to extract some important features of the target so that when the
same person appears again, the camera will recognize them.

 

The computer representation of
the tracking objects should be made for a proper
approach towards multi-object tracking. There have been developed many
strategies for that but this answer will cover the most important aspect of
required and possible solutions for this problem.

 

The
tracking problem.

 

By definition, the multi-object
tracking is a system that captures the configuration of multiple moving or
non-moving objects and determines separate identities in various frames one by
one. Many professionals are working to solve this multi-tracking problem by applying two primary approaches. The
first is when information is taken from inter-camera and second is associated
with input detection in the global phenomenon.

 

Before that, the important topics
for understanding are activity recognition and object recognition, tracking,
and detection. The rear is used to find the configurations and locations of the
captured objects belonging to a particular type. Recognition refers to the task
to identify objects with respect to the type of class it belongs to. The
classic example can be a car that has been identified by its manufacturer.

 

The tracking system is the
combination of the other two explained aspects of this system. The focus is
kept on identifying the frames by drawing correspondences from one frame to
another. This is usually done so that they can have consistent labels.

 

The ending task is to recognize
the activity over a period of time while
ignoring the fact that it is quite similar to the previous one. The only
difference one could make out is that the tracking follows continuous frames
whereas the end task is done to focus on one goal. This follows the tracking observations
in which people recognize activities that are often more complex than
previously done.

 

A good example is a handbag that
has been left behind by a person and it has been recognized by the surveillance
cameras.

 

Tracking
in offline and online systems.

 

The online tracking refers to the
process in which only the past and the information of the present are available
to process and get the results. The other one refers to the collection of
information to be viewed even without the access to the internet. This tracking system on online management is said to be real-time tracking in common terms. This system
gives the result of tracking almost instantly as it arrives.

 

There is a vast difference
between all the above-mentioned methods
that is online, real-time and offline.
Usually, the offline technique is not
quite useful for interactive purposes. It cannot produce quicker results.

 

The offline method is only used
when for the collection of traffic statistics and other related methods such as
video indexing. The offline system can
improve the tracking system because they can access saved videos on their hard drives.

 

Offline methods can be effective over the online technology since the time constraints in
the former do not exist. But there’s a catch, even online systems can act as if
they are standalone offline systems. This can be done by providing time delay
mechanisms. There are many models in multiple tracking systems that are managed
online. But few discussed below are still online systems.

Difficulty in the tracking
system.

 

Object
modeling is the most problematic aspect multi-object tracking system. The
computers still cannot define the identity
of an object with respect to computers. The good example is the tracking
program for a dog. If the programmer
desires to track a certain dog, he should program such a system by giving
detailed descriptions of that particular dog that differs from other objects.
The color, size, shape, breed and any birthmark
of the dog should be clearly described. He should be careful enough to avoid
making mistakes as much as possible. If something goes wrong, the program will
identify a cat as a dog.

 

This marks the
multi-object tracking little more difficult. The system should be able to deal
with the visual description of a particular object in an efficient way. In
object modeling, each and every object captured should be recognized in the correct and effective way. The varieties
of aspects may differ from textures, shapes, motion, background, and color.

 

Challenges in the generic
tracking system.

 

Even the
system successfully performs the object modeling function, the problem arises
when the appearance of the captured object changes, like a thief wearing a
different attire to fool the officials. One way the object modeling can tackle
this problem is by constructing 3D models and having a collection of few
templates based on appearance.

 

The second
method for this is by changing the shape
directly. Nonmoving objects are easy to track and identify. But humans change clothes every day, they deform. Such objects
require a much complex mechanism of the algorithm to track them effectively. The change
of hairstyle is a good example in this
case. This needs a high level of model preparation to identify high dimensional
objects.

 

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