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Multi-Object Tracking Based on Particle Filter and Data Association in Color Image Sequences

机译:基于粒子滤波和数据关联的彩色图像序列多目标跟踪

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摘要

Robust tracking of multi-objects is still challenging in real scenarios such as crowed scenes. In this paper a novel method in color image sequences is proposed for tracking multiple objects in non-cooperative situations. A system of independent particle filters with an adaptive motion model is used which tracks the moving objects under complex situations. Besides, in order to handle the conflicted situations, an integrated data association technique is exploited which adjusts the particle filters accordingly. Results have shown the good performance of the proposed method on various complex-situation image sequences.
机译:在真实场景(例如拥挤的场景)中,对多对象进行稳健的跟踪仍然具有挑战性。本文提出了一种彩色图像序列的新方法,用于在非合作情况下跟踪多个物体。使用具有自适应运动模型的独立粒子过滤器系统,该系统可以跟踪复杂情况下的运动对象。此外,为了处理冲突情况,开发了一种集成数据关联技术,该技术可以相应地调整粒子过滤器。结果表明,该方法在各种复杂情况的图像序列上均具有良好的性能。

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