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Pedestrian detection in video of outdoor condition

机译:户外条件视频中的行人检测

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摘要

Pedestrian detection is an important research field in computer vision and a lot of studies have been made to enhance the accuracy rate. However, there are some limitations such as most researchers used to study pedestrian detection with analyzing individual images, instead of considering the relationship of frames in videos. For dealing with pedestrian detection in the video, we present a new method to makes good use of both the image information in a single frame and the difference among contiguous frames. Our approach could improve the detection rate and reduce the false-positive ratio simultaneously, with reaching a speed of processing more than 60 frames per second. Moreover, as for the videos with bad quality and noise, our method also shows performance good enough for real surveillance cases. This paper also built a big dataset including 2414 videos, on which we test our method and achieve good performance. It provides a way to study more in pedestrian detection in videos for other researchers.
机译:行人检测是计算机视觉中的重要研究领域,已经进行了大量的研究以提高准确率。但是,存在一些局限性,例如大多数研究人员习惯于通过分析单个图像来研究行人检测,而不是考虑视频中帧的关系。为了处理视频中的行人检测,我们提出了一种新方法,可以充分利用单个帧中的图像信息以及连续帧之间的差异。我们的方法可以提高检测率并同时降低误报率,达到每秒处理60帧以上的速度。此外,对于质量和噪声较差的视频,我们的方法还显示出了足以用于实际监视案例的性能。本文还建立了一个包含2414个视频的大型数据集,我们在该数据集上测试了我们的方法并取得了良好的效果。它为其他研究人员提供了一种在视频中对行人检测进行更多研究的方法。

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