论文标题
分散行人跟踪的方向歧视特征表示
Orientation-Discriminative Feature Representation for Decentralized Pedestrian Tracking
论文作者
论文摘要
本文着重于使用传感器网络分散的行人跟踪的问题。行人跟踪的传统作品通常使用集中式框架，由于沟通带宽有限，对于机器人应用而言，这变得不那么实用。我们的论文提出了一种可以在传感器之间共享的沟通效率，定向歧视性特征来表征行人外观信息的表征。在这种代表性的基础上，我们的工作开发了一种跨传感器跟踪关联方法来实现分散的跟踪。对公开可用的数据集进行了广泛的评估，结果表明，我们提出的方法可改善多传感器跟踪的性能。
This paper focuses on the problem of decentralized pedestrian tracking using a sensor network. Traditional works on pedestrian tracking usually use a centralized framework, which becomes less practical for robotic applications due to limited communication bandwidth. Our paper proposes a communication-efficient, orientation-discriminative feature representation to characterize pedestrian appearance information, that can be shared among sensors. Building upon that representation, our work develops a cross-sensor track association approach to achieve decentralized tracking. Extensive evaluations are conducted on publicly available datasets and results show that our proposed approach leads to improved performance in multi-sensor tracking.
