Multiple object tracking (MOT) is a crucial task in computer vision, with a wide range of trackingalgorithms. Tracking and its complexity level depends on several factors, such as type of parameters beingtracked namely size, contour, position, velocity, and acceleration. It may also depend on number ofparameters used for tracking and the amount of prior knowledge about the target object. During trackingdifferent situations may arise such as, tracking of mobile object appearing for the first time in the scene.When representations of the object under consideration are available, it is feasible to learn it for the first time.Object tracking is an act of seeking for objects in successive frames of a video stream after learning has beencompleted. Even after so much research, MOT remains a difficult work since the object’s appearance canradically vary due to deformation, rotation out of plane, or changes in lighting conditions. Problem becomesmore challenging when tracking is to be done in dense places that consists of movable and immovable objects.

多目标跟踪(MOT)是计算机视觉中的一个关键任务，具有广泛的跟踪算法。跟踪及其复杂性水平取决于几个因素，例如被跟踪的参数类型，包括大小、轮廓、位置、速度和加速度。它还可能取决于用于跟踪的参数数量以及关于目标对象的先前知识量。在跟踪过程中可能出现不同的情况，例如，首次出现在场景中的移动对象的跟踪。当考虑对象的表示可用时，第一次学习它是可行的。目标跟踪是在完成学习后在视频流的连续帧中寻找对象的行为。即使经过了如此多的研究，MOT仍然是一项困难的工作，因为由于变形、平面外旋转或光照条件的变化，目标的外观可能会发生根本性的变化。当需要在包含可移动和不可移动对象的密集场所进行跟踪时，问题变得更加具有挑战性。