Efficient method for detecting and tracking moving objects in video

Nilesh J. Uke, P. Futane
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引用次数: 4

Abstract

Detection and tracking of moving object in the video has turned into a fascinating zone of exploration in the field of computer vision and has wide applications in fields like video surveillance, service robots, public security and target recognition. Although researches have proposed many approaches for object detection, robustness remains a huge challenge. In this paper, we proposed hybrid method of object detection using motion estimation and tracking by parallel kalman filter. Detection of the moving object is performed by analyzing the moving parts by corner and the shape feature extraction. The parallel kalman filter is used to tracks the object that is detected by calculating the motion estimation in video. The object tracking using the shape and the corner feature helps in providing the extract tracking of the object.
一种有效的视频中运动目标检测与跟踪方法
视频中运动物体的检测与跟踪已成为计算机视觉领域的一个引人入胜的探索领域,在视频监控、服务机器人、公共安全、目标识别等领域有着广泛的应用。尽管研究人员提出了许多目标检测方法,但鲁棒性仍然是一个巨大的挑战。本文提出了一种基于运动估计和并行卡尔曼滤波跟踪的混合目标检测方法。通过对运动部件进行角点分析和形状特征提取来实现运动目标的检测。通过计算视频中的运动估计,利用并行卡尔曼滤波对检测到的目标进行跟踪。利用形状和角的特征对目标进行跟踪,有助于对目标进行提取跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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