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The goal of this article is to review the state-of
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The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories,
and identify new trends. Object tracking, in general, is a challenging problem. Difficulties in tracking
objects can arise due to abrupt object motion, changing appearance patterns of both the object and the scene,
nonrigid object structures, object-to-object and object-to-scene occlusions, and camera motion. Tracking is
usually performed in the context of higher-level applications that require the location and/or shape of the
object in every frame. Typically, assumptions are made to constrain the tracking problem in the context of
a particular application. In this survey, we categorize the tracking methods on the basis of the object and
motion representations used, provide detailed descriptions of representative methods in each category, and
examine their pros and cons.Moreover, we discuss the important issues rel
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Implementation of an Automated Single Camera Objec
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Abstract - In the present work the concepts of dynamic template
matching and frame differencing have been used to implement a
robust automated single object tracking system. In this
implementation a monochrome industrial camera has been used
to grab the video frames and track an object. Using frame
differencing on frame-by-frame basis a moving object, if any, is
detected with high accuracy and efficiency. Once the object has
been detected it is tracked by employing an efficient Template
Matching algorithm. The templates used for the matching
purposes are generated dynamically. This ensures that any
change in the pose of the object does not hinder the tracking
procedure. To automate the tracking process the camera is
mounted on a pan-tilt arrangement, which is synchronized with a
tracking algorithm. As and when the object being tracked moves
out of the viewing range of the camera, the pan-t
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