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Efficient modified directional lifting-based discrete wavelet transform for moving object detection

机译:改进的基于方向提升的离散小波变换在运动目标检测中的应用

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Moving object detection is a fundamental task on intelligent video surveillance systems, because it provides a focus of attention for further investigation. Thus, video object segmentation, which extracts the shape information of moving object from a video sequence, is a key operation for surveillance system. In this study, the current state-of-the-art in moving objects segmentation for intelligent video surveillance has been surveyed. An efficient modified directional lifting-based 9/7 discrete wavelet transform (MDLDWT) structure is proposed to further reduce the computational cost and preserve the fine shape information in low resolution image. Although perfect moving object detection in a practical environment is a challenging task due to the vague object shape issues in the low resolution configuration, the experimental results document that the proposed low-complexity MDLDWT scheme can provide more precise detection rate for multiple moving objects, and the fine shape information can be effectively preserved for the real-time video surveillance applications in both indoor and outdoor environments.
机译:运动对象检测是智能视频监控系统的一项基本任务,因为它为进一步研究提供了关注的焦点。因此,从视频序列中提取运动对象的形状信息的视频对象分割是监视系统的关键操作。在这项研究中,已经调查了用于智能视频监控的运动对象分割的最新技术。提出了一种有效的基于方向提升的改进型9/7离散小波变换(MDLDWT)结构,以进一步降低计算成本并保留低分辨率图像中的精细形状信息。尽管在低分辨率配置中由于模糊的物体形状问题,在实际环境中进行完美的运动物体检测是一项艰巨的任务,但实验结果表明,提出的低复杂度MDLDWT方案可以为多个运动物体提供更精确的检测率,并且在室内和室外环境中,可以有效地保存精细形状信息,以用于实时视频监视应用程序。

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