使用机器学习的视频距离估计

S. D, Aravinda Cv, Roheet Bhatnagar
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引用次数: 0

摘要

在视频中,距离估计是指计算物体与摄像机之间的距离。摄像机记录下了一个人走在它前面的实时视频。当一个人站在摄像机前并开始在摄像机前行走时,实时视频被收集。从收集到的现场镜头中衍生出一系列视频帧。这些框架是分开处理的。每一帧都经过一种人脸检测方法。被检测的人脸被一个矩形包围。在检测到的人脸周围创建的矩形用于计算高度和宽度。这就是所谓的透视宽度。焦距是用透视宽度计算的。所提出的系统使用焦距来确定距离,一旦焦距被计算出来。用户现在可以走在系统前面,这样就可以进行距离估计了。基本目标是识别移动的人脸并计算其与相机的距离。在研究领域,距离估计是有用的。在执行方面,该计划利用了机器学习等尖端技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distance Estimation in Video using Machine Learning
In a video, distance estimate refers to calculating the distance between an object and the camera. The camera records the live video of a person walking in front of it. Live video is collected when a human stands in front of the camera and begins to walk in front of it. A sequence of video frames is derived from the collected live footage. These frames are handled separately. Each frame is subjected to a face detection method. The detected face is surrounded by a rectangle. The rectangle created around the detected face is used to calculate height and breadth. This is known as the perspective width. The focal length is calculated using the perspective width. The proposed system is using the focal length to determine distance once it has been calculated. The user can now walk in front of the system, which is now ready for distance estimation. The basic goal is to recognize a moving face and calculate its distance from the camera. In the realm of research, distance estimate is useful. For execution, the initiative makes use of cutting-edge technologies such as machine learning.
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