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首页> 外文会议>Conference on Real-Time Image Processing; 20080128-29; San Jose,CA(US) >Robust object detection based on radial reach correlation and adaptive background estimation for real-time video surveillance systems
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Robust object detection based on radial reach correlation and adaptive background estimation for real-time video surveillance systems

机译：基于径向距离相关性和自适应背景估计的实时视频监控系统鲁棒目标检测

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摘要

A method of real-time object detection for video surveillance systems has been developed. The method aims to realize robust object detection by using Radial Reach Correlation (RRC). We also apply a statistical background estimation to cope with dynamic and complex environments. The computational cost of RRC is higher than the simple subtraction method and the background estimation method based on statistical approach needs large memory. It is necessary to reduce the calculation cost in order to apply to an embedded image processing device. Our method is composed of two techniques: fast RRC algorithm and background estimation based on statistical approach with cumulative averaging process. As a result, without deterioration in detection accuracy, the processing time of object detection can be decreased to about 1/4 in comparison with normal RRC.
机译：已经开发了一种用于视频监视系统的实时对象检测的方法。该方法旨在通过使用径向距离相关（RRC）实现鲁棒的目标检测。我们还应用统计背景估计来应对动态和复杂的环境。 RRC的计算成本高于简单的减法，并且基于统计方法的背景估计方法需要大的存储空间。为了应用于嵌入式图像处理设备，必须降低计算成本。我们的方法由两种技术组成：快速RRC算法和基于统计方法的背景估计以及累积平均过程。结果，在不降低检测精度的情况下，与正常RRC相比，可以将物体检测的处理时间减少到大约1/4。

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