恶劣环境下多目标实时跟踪算法研究

提出一种在恶劣环境下能实时进行多目标跟踪的方法,相比于目前的监控系统,该方法能够更加精确地跟踪场景中的入侵目标,并且算法效率有了较大提升。首先,在动态背景建模codebook作为背景建模算法的基础上,对背景更新方法进行改进,使前景检测准确率相对于原算法有了很大提升,并且在主要性能上优于其他的主流背景建模算法。其次,本研究选用粒子滤波算法作为多目标跟踪方法,对重采样方法进行了较大改进,使之能在实时环境下保持粒子的有效性和多样性。实验证明该系统构建有较好效果,能在实际恶劣场景下进行多目标跟踪,并保持较好的检测和跟踪效果。

Multi-target real-time tracking method under harsh environment

A new method for multi-target real-time tracking system working under harsh environment was presented. Compared to the current researches in this field, this method could track the invasion target more accurately in the video surveillance scene, and the efficiency of the algorithm was improved greatly. First, based on the current mainstream background modeling method codebook algorithm, the background updating method was improved, which made the computation efficiency and the foreground of the codebook detection accuracy improved greatly compared to the original algorithm. The main performance was better than other mainstream background modeling algorithm. Then, a particle filter algorithm as the multi-target tracking method made large improvement for resampling method that could maintain the effectiveness and diversity of the particles in real time environment. Experiments proved this system could be used in multi-target real-time tracking under harsh environment and had effective performances.