论文标题
对象跟踪至少时空搜索
Object Tracking by Least Spatiotemporal Searches
论文作者
论文摘要
在城市中跟踪汽车或人对城市安全管理至关重要。我们如何通过大量相机记录中的时空搜索数量最少来完成任务？本文提出了一种名为IHMS的策略（在启发式时刻进行中间搜索）：我们确定哪个时刻是根据启发式指标进行搜索的最佳时刻，然后在那一刻，以预测的概率为止，以一个降低的顺序搜索位置，直到搜索搜索命中；迭代此步骤，直到我们获得对象的当前位置为止。在实验中比较了五种搜索策略，而IHMS已被验证为最有效的，可以节省多达1/3的总成本。该结果提供了一个证据，表明“在中间时刻搜索可以节省成本”。
Tracking a car or a person in a city is crucial for urban safety management. How can we complete the task with minimal number of spatiotemporal searches from massive camera records? This paper proposes a strategy named IHMs (Intermediate Searching at Heuristic Moments): each step we figure out which moment is the best to search according to a heuristic indicator, then at that moment search locations one by one in descending order of predicted appearing probabilities, until a search hits; iterate this step until we get the object's current location. Five searching strategies are compared in experiments, and IHMs is validated to be most efficient, which can save up to 1/3 total costs. This result provides an evidence that "searching at intermediate moments can save cost".
