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Gait Silhouette Extraction from Videos Containing Illumination Variates

机译:从包含光照变化的视频中步态轮廓提取

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We present a heuristic method to automatically adjust pixel intensity per frame from video by analyzing its colour type and level of brightness before initiating silhouette extraction phase. As this is performed at the pre-processing phase, our proposed method aims to show that it is an improvement or solution for videos containing inconsistency of illumination compared to normal background subtraction. We are introducing two modules; a prior processing module and an illumination modeling module. The prior processing module consists of resizing and smoothing operations on related frame in order to accommodate the subsequent module. The illumination modeling module manipulates pixel values in each frame to improve silhouette extraction for a video containing inconsistency of illumination. This proposed method is tested on 1072 videos including videos from an external KTH database.
机译:我们提出一种启发式方法,通过在启动轮廓提取阶段之前分析视频的颜色类型和亮度级别,来自动调整视频每帧的像素强度。由于这是在预处理阶段执行的,因此我们提出的方法旨在表明,与正常背景减法相比,它是对包含照明不一致性的视频的改进或解决方案。我们将介绍两个模块;预先处理模块和照明建模模块。先前的处理模块包括对相关帧的大小调整和平滑操作,以适应后续的模块。照明建模模块处理每个帧中的像素值,以改善包含照明不一致性的视频的轮廓提取。在包括外部KTH数据库的视频在内的1072个视频上测试了此提议的方法。

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