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Tracking Method in Consideration of Existence of Similar Object around Target Object

机译:考虑目标物体周围相似物体存在的跟踪方法

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Tracking methods based on the particle filter uses frequently the appearance information of the target object to calculate the likelihood. The method using it often fails in tracking when the target object intersects with other objects with similar appearances. We propose a new approach for tracking objects with similar patterns in a video sequence taken by a moving camera. The proposed method based on the particle filter is robust to the intersection with other objects. Two state transition functions are defined for robust tracking. The method changes the function depending on the situation. In addition, the likelihood is calculated by using four factors which are the information of the color, the velocity, the distance between the objects and the values calculated by the probability background model. The method detects objects which are similar to the target object and which exist around the target object. This prevents the method from tracking other object mistakenly. Results are demonstrated by experiments using real video sequences.
机译:基于粒子滤波器的跟踪方法经常使用目标对象的外观信息来计算似然度。使用该方法的方法通常无法跟踪目标对象何时与其他外观相似的对象相交。我们提出了一种新方法,用于跟踪移动摄像机拍摄的视频序列中具有相似模式的对象。所提出的基于粒子滤波器的方法对于与其他对象的相交具有鲁棒性。为稳健跟踪定义了两个状态转换函数。该方法根据情况改变功能。另外,通过使用四个因素来计算似然度,这四个因素是颜色,速度,物体之间的距离以及由概率背景模型计算出的值的信息。该方法检测与目标对象相似并且存在于目标对象周围的对象。这样可以防止该方法错误地跟踪其他对象。通过使用真实视频序列的实验证明了结果。

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