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A Simplified Error Model for Height Estimation using a Single Camera

机译:单个摄像机的高度估计简化错误模型

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Intelligent solutions for video surveillance require reliable object features for robust tracking. Surveillance cameras are generally low resolution and hence impose restrictions on the ability to identify sufficient features and descriptors for effective tracking. In such applications, reliable estimate of the object height from a single uncalibrated camera can prove to be a very useful feature. Several approaches have been developed to obtain height information of an object from image sequences, but are limited in their utility due to errors arising from varying image and object properties. In this paper, we present a simplified error model dependent on the location of the object in the image and the estimated camera height. Further, the developed model is used to obtain reliable height estimates of objects in different image sequences and the result is compared to estimates obtained without the use of the model. Significant reduction in error associated with the measurement is observed while making the estimate independent of camera and object variations. We then demonstrate its utility in object tracking.
机译:用于视频监控的智能解决方案需要可靠的对象特征来进行鲁棒跟踪。监控摄像机通常是低分辨率,因此对识别有效跟踪的足够特征和描述符的能力施加限制。在这种应用中,来自单个未校准相机的对象高度的可靠估计可以证明是一个非常有用的特征。已经开发了几种方法来从图像序列获取对象的高度信息,但由于从不同图像和对象属性产生的错误,其实用程序受到限制。在本文中,我们介绍了一种简化的错误模型,依赖于图像中对象的位置和估计的相机高度。此外,开发的模型用于获得不同图像序列中的物体的可靠高度估计,并将结果与​​在不使用模型的情况下获得的估计进行比较。观察到与测量相关的误差显着降低,同时使估计无关,与相机和对象变化无关。然后,我们展示其在对象跟踪中的实用程序。

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