Object tracking is one of the main fields within computer vision. Amongst various methods/ approaches for object detection and tracking, the background subtraction approach makes the detection of object easier. To the detected object, apply the proposed block matching algorithm for generating the motion vectors. The existing diamond search (DS) and cross diamond search algorithms (CDS) are studied and experiments are carried out on various standard video data sets and user defined data sets. Based on the study and analysis of these two existing algorithms a modified diamond search pattern (MDS) algorithm is proposed using small diamond shape search pattern in initial step and large diamond shape (LDS) in further steps for motion estimation. The initial search pattern consists of five points in small diamond shape pattern and gradually grows into a large diamond shape pattern, based on the point with minimum cost function. The algorithm ends with the small shape pattern at last. The proposed MDS algorithm finds the smaller motion vectors and fewer searching points than the existing DS and CDS algorithms. Further, object detection is carried out by using background subtraction approach and finally, MDS motion estimation algorithm is used for tracking the object in color video sequences. The experiments are carried out by using different video data sets containing a single object. The results are evaluated and compared by using the evaluation parameters like average searching points per frame and average computational time per frame. The experimental results show that the MDS performs better than DS and CDS on average search point and average computation time.
-Object tracking is one of the vital fields of computer vision that detects the moving object from a video sequence. Object detection is used to detect the object present in the video and to find the exact location of that object. The object tracking can be applied in various fields that include video surveillance, robot vision, traffic monitoring, automated civil or military surveillance system, traffic monitoring, human-computer interaction, vehicle navigation, biomedical image analysis, medical imaging and much more. The object tracking algorithm requires tracking the object in each frame of the video. A common approach is to use the background subtraction, which eliminates the common static background, resulting into foreground region showing the presence of the desired object. Block matching technique is the most popular technique for computing the motion vectors between the two frames of video sequences and different searching techniques are available to compute motion vectors between frames. Still, there is a scope for improvement in modifying or developing a new shape pattern for block matching motion estimation to find out and track the object in the video. This paper presents the several object detection and tracking methods and how block matching can be used to track object from a video.
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