Crane tracking and monitoring system based on TLD algorithm
作者： Hongjun Sun , Tao Yu
DOI: 10.1109/I2MTC.2016.7520351
关键词: Robustness (computer science) 、 Thermoluminescent dosimeter 、 Engineering 、 Particle filter 、 Tracking system 、 Monitoring system 、 Algorithm 、 Particle filtering algorithm
摘要: Aiming at tracking performance of real-time and robustness crane monitoring system, current target methods are contrasted in this paper, such as Tracking-Learning-Detection (TLD) algorithm, MeanShift particle filter. Experimental results show that filter algorithm have the advantage over TLD performance. However, can adapt to transformation with preferable self-learning capability. And enables re-track object even if is sheltered or missed momently. Therefore, system based on not only detect track accurately but also be superior another two algorithms robustness.
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