A reliable string kernel based approach for solving queries by sketch

In this paper we propose a novel and efficient method for solving queries by sketch in traffic scenarios, aiming to find the k nearest neighbor trajectories to the one hand drawn by the human operator. Each trajectory is represented as a sequence of symbols, namely a string, and it is stored into a k-d tree by taking into account the similarity between trajectories, evaluated by a global fast alignment kernel. The experimentation has been conducted over the standard MIT trajectories dataset and results confirm the effectiveness and the robustness of the proposed approach.