Comparative Study of Face and Person Detection algorithms: Case Study of tramway in Lyon

Hatem Belhassen (1) , El-Bay Bourennane (2) , Fresse, Virginie (3)

1 Beamtek SAS
2 ImViA - Imagerie et Vision Artificielle [Dijon]
3 LHC - Laboratoire Hubert Curien

Moving object detection is one of the most important and challenging task in video surveillance and computer vision applications. Applying it in an industrial context requires taking into account parameters that are not necessarily considered in a theoretical context. We present here a brief review of numerous face and object detection algorithms and techniques that could be applied in our crowded application context. The chosen solution was embedded into the tramway.

Mots clés: object detection algorithms; object detection; numerous face; crowded application context; image motion analysis; face recognition; video surveillance; tramway; person detection algorithms; Cameras; Prediction algorithms; Feature extraction; Detectors; Face; Lyon; computer vision applications; face detection algorithms; Face detection; person detection; smart transportation; crowded scene; data sets; industrial context

Domaines: Algorithme et structure de données [cs.DS]; Intelligence artificielle [cs.AI]; Traitement du signal et de l'image [eess.SP]; Vision par ordinateur et reconnaissance de formes [cs.CV]

Hatem Belhassen, El-Bay Bourennane, Fresse, Virginie. Comparative Study of Face and Person Detection algorithms: Case Study of tramway in Lyon. 3rd International Conference on Advanced Systems and Emergent Technologies (IC_ASET'2019) 19-22 March 2019, Hammamet-Tunisia, Association des Spécialistes Electriciens de Tunisie, Mar 2019, Hammamet, Tunisia. ⟨10.1109/ASET.2019.8871003⟩. ⟨hal-02140525⟩