改进霍恩-施恩克算法，提升图像运动估计精度与收敛速度。
Investigating Optical Flow Computation: From Local Methods to a Multiresolution Horn-Schunck Implementation with Bilinear Interpolation
- 采用多分辨率框架结合双线性插值优化全局光流计算。
- 在不同图像条件下显著提升运动估计准确率与收敛速度。
- 适合计算机视觉中运动分析与视频处理研究者参考。
本文针对光流计算中的局部与全局方法进行应用分析，重点研究霍恩-施恩克算法。探讨了卢卡斯-卡纳德等局部方法和霍恩-施恩克等全局方法的理论与实践特性。同时，实现了一种基于双线性插值与延拓的多分辨率霍恩-施恩克算法，以提升精度与收敛性能。研究评估了这些策略在不同图像条件下的运动估计效果。
原文摘要 · Abstract (English)
This paper presents an applied analysis of local and global methods, with a focus on the Horn-Schunck algorithm for optical flow computation. We explore the theoretical and practical aspects of local approaches, such as the Lucas-Kanade method, and global techniques such as Horn-Schunck. Additionally, we implement a multiresolution version of the Horn-Schunck algorithm, using bilinear interpolation and prolongation to improve accuracy and convergence. The study investigates the effectiveness of these combined strategies in estimating motion between frames, particularly under varying image conditions.
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