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This paper proposes a distance measurement between pedestrian trajectories. This distance is used in a clustering method aiming to detect lanes of pedestrians in experimental data. The main ingredient is to take full advantage of the time sequence available. A study of the sensitivity of the clustering to the parameters shows it is possible to choose a stable set of parameters. We also define an order index based on the concept of entropy. The potential of this index is illustrated in the case of pedestrian lane detection.

LANE DETECTION IN PEDESTRIAN MOTION AND ENTROPY-BASED ORDER INDEX