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Tracking Moving Objects in Video

机译：跟踪视频中的移动对象

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—Object tracking is a well-studied problem in computer vision and has many practical applications. The problem and its difficulty depend upon several factors such as the knowledge about the target object, its quantity and type of parameters being tracked. Although there has been some success with building trackers for specific object classes such as human, face, mice etc. Tracking generic objects has remained challenging issue because an object can drastically change its appearance when deforming, rotating out of plane or when the illumination of the scene changes. Especially in the videos which are not clear in its original form i.e. the video which requires enhancement and its quality has to be improved. Here in the proposed work different algorithms are carried out to detect the generic objects such as the non-rigid objects and the deformable objects which are in occlusion, (i.e. in a cluttered environment) not only in the images which contain some sort of objects but also from the images which contains numerous objects which are unseen so as to improve the tracking efficiency. By doing this, the objects which are non-rigid and changing in nature can also be predicted in a perfect manner so that the computational complexity can be reduced, reliability, accuracy, and efficiency can be improved.
机译：-Object跟踪是计算机视觉中的一个良好的问题，并且具有许多实际应用。问题及其困难取决于若干因素，例如对目标对象的知识，其数量和类型的参数进行跟踪。虽然有一些成功的构建跟踪器，用于特定对象类，如人，脸，小鼠等。跟踪通用物体存在挑战性问题，因为在变形时，物体可以大大改变其外观，旋转飞出平面或当照明时场景变化。特别是在其原始形式的视频中不清楚的视频中，必须改善需要提高的视频及其质量。这里，在所提出的工作中，执行不同的算法，以检测诸如非刚性物体的通用物体和在闭塞中的可变形物体，（即，在杂乱的环境中）不仅在包含某种物体的图像中，但是还来自包含许多未经看来的物体的图像，以提高跟踪效率。通过这样做，也可以以完美的方式预测非刚性和性质变换的对象，以便可以降低计算复杂性，可靠性，准确性和效率。

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