Precise Tracking of Moving Objects Using KLT, Sift and DBSCAN Algorithms
Subject Areas : electrical and computer engineeringKeywords: Moving objects tracking DBSCAN KLT Sift,
Abstract :
Detecting and tracking of moving objects is an important task in analyzing videos. In this paper, we propose a new method for tracking several concurrent moving objects of fixed camera. In the proposed method, at each stage, the location of moving objects in front of camera view is obtained information between two current and previous frames. In each step, Sift’s edge points is obtained based on previous frame and to get the correspondence of these feature points by the use of KLT feature point correspondence algorithm on the current frame. Then having correspondent feature points between two sequence frames, we would estimate the distance by eliminating partial or fixed moving feature points related to moving objects. The classification of labeled features as moving objects is done using DBSCAN clustering algorithm into different clusters. By this method and on each moment, the situation of all existing moving objects in camera view which has got by one by one correspondence between these objects, is determined. The obtained results of the proposed method shows a high degree of accuracy and acceptable consuming time to track moving objects.
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