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A Fast-RCNN Implementation for Human Silhouette Detection in Video Sequences

机译:视频序列中的人类轮廓检测的快速rcnn实现

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The intention of this article is to implement a system of detection and segmentation of human silhouettes, the above mentioned tasks present a great challenge in security topics and innovation, in the last years and mainly on automated video surveillance systems, which require understanding the presence and human interaction in video sequences, e.g. Human Computer Interaction (HCI), Human Behaviour comprehension, Human fall detection, among others, but the most important is behavioural biometrics, this paper tackles the common step in these research areas: the Human silhouette extraction through the bounding box. To evaluate the proposed system, standardized databases where used and also proper videos are obtained trying to emulate real-world scenarios, where the quality and the distance are factors that have demonstrated challenges for the detection with computer vision and machine learning.
机译:本文的意图是实施人类剪影的检测和分割系统,上述任务在安全主题和创新方面存在巨大挑战,在过去几年,主要是在自动视频监控系统上,这需要了解存在和 视频序列中的人类相互作用,例如 人类计算机互动(HCI),人类行为理解,人类跌倒检测,等等,但最重要的是行为生物识别学,本文解决了这些研究领域的共同步骤:通过边界箱提取人体轮廓提取。 为了评估所拟议的系统,获得使用的标准化数据库以及在尝试模拟现实世界场景的情况下获得的标准化数据库,其中质量和距离是通过计算机视觉和机器学习对检测挑战的因素。

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