Depth estimation and implementation on the DM6437 for panning surveillance cameras

M. Asif, J. Soraghan
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引用次数: 6

Abstract

Real-time efficient video analytics (VA) for surveillance system requires “in-camera” or “at camera edge” decision-making. Video Analytics is required to work on good resolution footage in order to register tiny but important information that may otherwise be lost during subsequent compression process, especially in temporally exploited streams. This paper presents a novel approach to estimate 3D location coordinates of selected control points from panning camera footage. The two frames at different panning angles are considered to be two images captured from two different coplanar viewpoints with some translational distance between their optical centers. To simulate panned images as coplanar the information required is the panning angle. With the help of the panning angle transformational matrix two image planes are calculated. The approach developed here will help extract motion descriptors, including and not limited to, motion activity and direction of motion activity. The performance of the algorithm is evaluated in the paper using several test sequences. This paper provides a comprehensive implementation issues onto TI DaVinci platform.
移动监控摄像机DM6437的深度估计与实现
监控系统的实时高效视频分析(VA)需要“摄像机内”或“摄像机边缘”决策。视频分析需要在高分辨率的镜头上工作,以便记录微小但重要的信息,否则这些信息可能会在随后的压缩过程中丢失,特别是在临时利用的流中。本文提出了一种从平移摄像机镜头中估计选定控制点的三维位置坐标的新方法。不同平移角度的两幅图像被认为是从两个不同的共面视点捕获的两幅图像,它们的光学中心之间有一定的平移距离。要将平移后的图像模拟为共面,所需的信息是平移角度。利用平移角度变换矩阵计算了两个像面。这里开发的方法将有助于提取运动描述符,包括但不限于运动活动和运动活动的方向。本文用几个测试序列对算法的性能进行了评价。本文提供了一个全面的在TI达芬奇平台上的实现问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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