Fast Camera Motion Estimation utilizing Mode and Directional Self Information in the Compressed Domain

N. Brinda, M. Okade
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Abstract

This paper presents a fast camera motion estimation technique based on analyzing the magnitude and orientation histograms obtained from the compressed domain motion vectors. The magnitude and orientation histograms obtained from the compressed domain motion vectors are analyzed separately in order to determine the outlier thresholds. The statistical mode of the magnitude and orientation histograms combined with the Directional Self Information of the orientation histogram serves as the threshold selection criteria for the outliers based on which the inlier motion vectors are identified. The inlier motion vectors are then fed to the least square estimator which calculates the camera motion parameters. Comparative analysis is carried out with three existing state-of-the-art camera motion estimation methods to establish the proposed technique. Our experiments show that the proposed technique is computationally faster at the same time retaining its accuracy in determining the camera motion parameters.
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基于压缩域模式和方向自信息的快速摄像机运动估计
本文提出了一种基于对压缩域运动矢量的大小直方图和方向直方图进行分析的快速摄像机运动估计技术。分别对压缩域运动矢量得到的幅度直方图和方向直方图进行分析,确定离群阈值。大小直方图和方向直方图的统计模式结合方向直方图的方向自信息作为离群点的阈值选择准则,根据离群点识别内线运动向量。然后将内层运动矢量馈送到最小二乘估计器,最小二乘估计器计算相机运动参数。通过与现有的三种最先进的摄像机运动估计方法进行比较分析,以确定所提出的技术。实验表明,该方法在保证确定摄像机运动参数的准确性的同时,计算速度更快。
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