An Advanced Motion Detection Algorithm with Video Quality Analysis for Video Surveillance Systems
An Advanced Motion Detection Algorithm with Video Quality Analysis for Video Surveillance Systems
复制标题
DOI：
10.1109/tcsvt.2010.2087812
复制
发表时间：
2011-01-01
影响因子：
8.4
通讯作者：
Huang, Shih-Chia
中科院分区：
文献类型：
--
作者：
Huang, Shih-Chia
运动检测是提取运动目标信息的第一个基本过程，它在跟踪、分类、识别等功能中发挥着重要的作用，本文提出了一种新的、精确的运动检测方法。我们的方法实现了完整的检测移动对象，涉及三个重要的建议模块：背景建模（BM）模块，报警触发（AT）模块，和对象提取（OE）模块。对于我们提出的BM模块，一个独特的两阶段的背景匹配过程进行快速匹配，然后进行准确的匹配，以产生最佳的背景像素的背景模型。接下来，我们提出的AT模块消除了整个背景区域的不必要的检查，允许后续的OE模块只处理包含移动对象的块。最后，OE模块形成二进制对象检测掩码，以实现运动对象的高度完整的检测。我们提出的（PRO）方法产生的检测结果进行了定性和定量分析，通过目视检查和准确性，沿着与其他国家的最先进的方法产生的结果进行比较。分析表明，我们的PRO方法具有更高的有效性，优于其他方法，F-1度量准确率高达53.43%。
Motion detection is the first essential process in the extraction of information regarding moving objects and makes use of stabilization in functional areas, such as tracking, classification, recognition, and so on. In this paper, we propose a novel and accurate approach to motion detection for the automatic video surveillance system. Our method achieves complete detection of moving objects by involving three significant proposed modules: a background modeling (BM) module, an alarm trigger (AT) module, and an object extraction (OE) module. For our proposed BM module, a unique two-phase background matching procedure is performed using rapid matching followed by accurate matching in order to produce optimum background pixels for the background model. Next, our proposed AT module eliminates the unnecessary examination of the entire background region, allowing the subsequent OE module to only process blocks containing moving objects. Finally, the OE module forms the binary object detection mask in order to achieve highly complete detection of moving objects. The detection results produced by our proposed (PRO) method were both qualitatively and quantitatively analyzed through visual inspection and for accuracy, along with comparisons to the results produced by other state-of-the-art methods. The analyses show that our PRO method has a substantially higher degree of efficacy, outperforming other methods by an F-1 metric accuracy rate of up to 53.43%.