Real-Time Object Detection with Adaptive Background Model and Margined Sign Correlation
Real-Time Object Detection with Adaptive Background Model and Margined Sign Correlation
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DOI：
10.1007/978-3-642-12297-2_7
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发表时间：
2008-11
期刊：
影响因子：
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通讯作者：
A. Yamamoto;Y. Iwai
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文献类型：
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作者：
A. Yamamoto;Y. Iwai
近年来，在各种条件下使用复杂的方法检测精度有了显著的提高，但是这些方法需要大量的计算成本，并且难以实时应用。本文提出了一种使用图形处理单元（GPU）的室外环境中的目标检测实时系统。自适应背景模型和边缘符号相关这些算法可以鲁棒地检测运动目标和去除阴影区域实验结果表明，该系统的实时性能。
In recent years, the detection accuracy has significantly improved under various conditions using sophisticated methods However, these methods require a great deal of computational cost, and have difficulty in real-time applications In this paper, we propose a real-time system for object detection in outdoor environments using a graphics processing unit (GPU) We implement two algorithms on a GPU: adaptive background model, and margined sign correlation These algorithms can robustly detect moving objects and remove shadow regions Experimental results demonstrate the real-time performance of the proposed system.