Fast and viewpoint robust human detection for SAR operations

Paul Blondel (1) , Alex Potelle (1) , Claude Pégard (1) , Rogelio Lozano (2)

1 MIS - Modélisation, Information et Systèmes - UR UPJV 4290
2 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]

There are many advantages in using UAVs for search and rescue operations. However, detecting people from a UAV remains a challenge: the embedded detector has to be fast enough and viewpoint robust to detect people in a flexible manner from aerial views. In this paper we propose a processing pipeline to 1) reduce the search space using infrared images and to 2) detect people whatever the roll and pitch angles of the UAV's acquisition system. We tested our approach on a multimodal aerial view dataset and showed that it outperforms the Integral Channel Features (ICF) detector in this context. Moreover, this approach allows real-time compatible detection.

Mots clés: drone; viewpoint robust; search and rescue; uav; human detection

Domaines: Automatique / Robotique; Traitement du signal et de l'image [eess.SP]

Paul Blondel, Alex Potelle, Claude Pégard, Rogelio Lozano. Fast and viewpoint robust human detection for SAR operations. IEEE international Symposium on Safety, Security and Rescue Robotics (SSRR 2014), Oct 2014, Toyako-cho, Japan. pp.1-6. ⟨hal-01086135⟩