基于wisard的CDnet方法

2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence Pub Date : 2013-09-08 DOI:10.1109/BRICS-CCI-CBIC.2013.37

Massimo De Gregorio, Maurizio Giordano

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引用次数: 19

摘要

在本文中，我们提出了一种基于wisard的系统(CwisarD)，该系统针对同一场景在不同时间拍摄的多幅图像中的变化检测问题，特别是静态摄像机拍摄的同一视图视频中的运动检测问题。虽然提出的无权重神经方法非常简单和直接，但它在ChangeDetection.net基准数据集(CDnet)上与其他方法进行挑战时提供了非常好的结果。

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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A WiSARD-Based Approach to CDnet

In this paper, we present a WiSARD-based system (CwisarD) facing the problem of change detection (CD) in multiple images of the same scene taken at different time, and, in particular, motion in videos of the same view taken by a static camera. Although the proposed weightless neural approach is very simple and straightforward, it provides very good results in challenging with others approaches on the ChangeDetection.net benchmark dataset (CDnet).

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2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence

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