利用KLT辅助平均位移目标跟踪器进行目标跟踪(ICCAS 2014)

2014 14th International Conference on Control, Automation and Systems (ICCAS 2014) Pub Date : 2014-12-18 DOI:10.1109/ICCAS.2014.6987974

Sun-Ho Kim, Jungho Kim, Youngbae Hwang, Byoung-Tae Choi, J. Yoon

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引用次数: 1

摘要

本文提出了一种新的目标跟踪算法，该算法将基于颜色的均值位移和基于特征的光流方法相结合。为了以互补的方式利用两种方法，我们基于颜色直方图和KLT跟踪特征迭代计算mean-shift向量。在实验中，我们在具有代表性的基准序列中展示了部分遮挡和严重外观变化的改进性能。

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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Object tracking using KLT aided mean-shift object tracker (ICCAS 2014)

In this paper, we present a new object tracking algorithm which integrates color-based mean-shift and feature-based optical flow methods. To utilize two approaches in the complimentary manner, we iteratively compute the mean-shift vector based on color histograms and tracked features by KLT. In the experiments, we show the improved performance for partial occlusion and severe appearance changes in the representative benchmark sequences.

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来源期刊

2014 14th International Conference on Control, Automation and Systems (ICCAS 2014)

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