02459nas a2200253   4500000000100000000000100001008004100002260001200043653002200055653002700077653002900104653003500133653002900168100002000197700002300217700002100240700002100261245010700282856009600389300001000485490000600495520169000501022001402191       2018                            d  c06/201810aMotion Estimation10aBackground Subtraction10aBlock Matching Algorithm10aCross Diamond Search Algorithm10aDiamond Search Algorithm1 aShailesh Kamble1 aNileshsingh Thakur1 aApurva Samdurkar1 aAkshay Patharkar00aObject Detection and Tracking using Modified Diamond Search Block Matching Motion Estimation Algorithm  uhttp://www.ijimai.org/journal/sites/default/files/files/2017/10/ijimai_5_1_10_pdf_12412.pdf  a73-850 v53 aObject 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.  a1989-1660