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Shadow-aware object-based video processing

机译:阴影感知的基于对象的视频处理

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摘要

Local illumination changes due to shadows often reduce the quality of object-based video composition and mislead object recognition. This problem makes shadow detection a desirable tool for a wide range of applications, such as video production and visual surveillance. In this paper, an algorithm for the isolation of video objects from the local illumination changes they generate in real world sequences when camera, illumination and the scene characteristics are not known is presented. The algorithm combines a change detector and a shadow detector with a spatiotemporal verification stage. Colour information and spatio-temporal constraints are embedded to define the overall algorithm. Colour information is exploited in a selective way. First, relevant areas to analyse are identified in each image. Then, the colour components that carry most of the needed information are selected. Finally, spatial and temporal constraints are used to verify the results of the colour analysis. The proposed algorithm is demonstrated on both indoor and outdoor video sequences. Moreover, performance comparisons show that the proposed algorithm outperforms state-of-the-art methods.
机译:由于阴影引起的局部照明变化通常会降低基于对象的视频合成的质量并误导对象识别。这个问题使阴影检测成为视频制作和视觉监控等广泛应用的理想工具。在本文中,提出了一种算法,用于将视频对象与它们在真实世界序列中生成的局部照明变化隔离开来,该摄像机在不知道摄像机,照明和场景特征的情况下。该算法将变化检测器和阴影检测器与时空验证阶段结合在一起。嵌入颜色信息和时空约束以定义整体算法。颜色信息是有选择地利用的。首先,在每个图像中确定要分析的相关区域。然后,选择带有大多数所需信息的颜色分量。最后,使用空间和时间约束来验证颜色分析的结果。在室内和室外视频序列上都演示了该算法。此外,性能比较表明,所提算法优于最新方法。

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