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View-Based and Visual-Attention-Based Background Modeling for Detecting Frequently and Infrequently Moving Objects for Video Summarization

机译:基于视图和基于视觉注意的背景建模,用于检测频繁和不频繁移动的对象以进行视频摘要

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The real-time face detection (FD) algorithm is proposed to find faces in the images as well as videos. Besides face regions, this algorithm also finds the exact localities of the face parts like lips and eyes. Initially, skin pixels are extracted centered on the rules of simple quadratic polynomial model. By introducing small modifications, this polynomial model (PM) could be applied for extracting the lips. The merits of adopting these two identical PMs are two-fold. Firstly, computation time is saved. Secondly, these extraction processes could be executed at the same time on one scan of the video or image frame. Subsequent to skin and lips, the eyes are extorted. Later, the algorithm eliminates the falsely extorted parts by validating with rules taken as of the spatial and geometrical relationships (SGR) of face parts. At last, the exact face regions are ascertained accordingly. As per the experiential outcomes, the proposed algorithm evinces preeminent task in respect of accuracy and speed for FD with huge differences in color, size, shape, expressions, and angles.
机译:提出了一种实时人脸检测(FD)算法,可以在图像和视频中找到人脸。除了脸部区域,该算法还可以找到嘴唇和眼睛等脸部部位的确切位置。最初,以简单二次多项式模型的规则为中心提取皮肤像素。通过引入小的修改,该多项式模型(PM)可以用于提取嘴唇。采用这两个相同的PM的优点是双重的。首先,节省了计算时间。其次,这些提取过程可以在视频或图像帧的一次扫描上同时执行。在皮肤和嘴唇之后,眼睛被勒索。后来,该算法通过使用脸部部位的空间和几何关系(SGR)所采用的规则进行验证,从而消除了错误敲诈的部位。最后,确切地确定面部区域。根据实验结果,提出的算法在颜色,大小,形状,表达式和角度方面存在巨大差异,从而在FD的准确性和速度方面表现出了卓越的任务。

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