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In recent years, demand for pedestrian detection using inex pensive low-resolution LIDAR (LIght Detection And Ranging) is increasing, as it can be used to prevent tra ffic accidents involving pedestrians. However, it is difficult to detect pedestrians from a low-resolution (sparse) p oint-cloud obtained by a low-resolution LIDAR. In this paper, we propose multi-frame features calculated b y integrating point-clouds over multiple frames for increasing the point-cloud resolution, and extracting the ir temporal changes. By combining these features, the accuracy of the pedestrian detection from low-resoluti n point-clouds can be improved. We conducted experiments using LIDAR data obtained in actual tra ffic environments. Experimental results showed that the proposed method could detect pedestrians accurately from l ow-resolution LIDAR data.

Can We Detect Pedestrians using Low-resolution LIDAR? - Integration of Multi-frame Point-clouds