建模运动预测技术:线性和二次样条vs循环队列向量方法

J. T. Tello-Martínez, O. Starostenko, V. Alarcón-Aquino, W. Hernandez
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引用次数: 0

摘要

本文提出了两种用于有限图像序列中目标运动预测的新方法的建模和性能分析。特别地,这些提出的方法是基于线性或二次样条和循环队列向量对应。他们使用了作者提出的两种基本的运动检测技术,通过包络或质心网格的表示来提供对象跟踪。通过几个模拟运动学实验,对所提出的运动预测方法的性能和效率进行了评估,这些模拟运动学实验包括匀速运动和加速运动,以及抛物线运动和圆周运动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling Motion Prediction Techniques: Linear and Quadratic Splines vs Circular-Queue Vector Approach
The modeling and performance analysis of two novel approaches for motion prediction of objects in a limited sequence of images is presented in this paper. Particularly, these proposed approaches are based on linear or quadratic splines and on circular-queue vector correspondence. They use two basic motion detection techniques also proposed by authors that provide object tracing by its representation by envelope or by mass center grid. The performance and efficiency of the proposed motion prediction approaches are evaluated applying several simulated kinematics experiments either with constant velocity and accelerated motion, or with parabolic and circular motion.
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