2D Image head pose estimation via latent space regression under occlusion settings

José Celestino, Manuel Marques, Jacinto C. Nascimento, João Paulo Costeira

Abstract: Highlights•Occlusion robust HPE framework relying on latent space regression with multi-loss.•Results surpass state-of-the-art methods in face images with occlusion and are similar without occlusion.•Ablation study on occlusion size reveals 39% error decrease for large occlusions.•Application in real scenario: feeding robot for people with upper body impairment.•Synthetic occlusion generation and application to existing head pose datasets.