Occlusion and Motion Reasoning for Long-term Tracking - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

Occlusion and Motion Reasoning for Long-term Tracking

Karteek Alahari
Cordelia Schmid
  • Fonction : Auteur
  • PersonId : 831154

Résumé

Object tracking is a reoccurring problem in computer vision. Tracking-by-detection approaches, in particular Struck (Hare et al., 2011), have shown to be competitive in recent evaluations. However, such approaches fail in the presence of long-term occlusions as well as severe viewpoint changes of the object. In this paper we propose a principled way to combine occlusion and motion reasoning with a tracking-by-detection approach. Occlusion and motion reasoning is based on state-of-the-art long-term trajectories which are labeled as object or background tracks with an energy-based formulation. The overlap between labeled tracks and detected regions allows to identify occlusions. The motion changes of the object between consecutive frames can be estimated robustly from the geometric relation between object trajectories. If this geometric change is significant, an additional detector is trained. Experimental results show that our tracker obtains state-of-the-art results and handles occlusion and viewpoints changes better than competing tracking methods.
Fichier principal
Vignette du fichier
tracking.pdf (2.29 Mo) Télécharger le fichier
Vignette du fichier
tracking.jpg (240.22 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Format : Figure, Image
Loading...

Dates et versions

hal-01020149 , version 1 (07-07-2014)

Identifiants

Citer

Yang Hua, Karteek Alahari, Cordelia Schmid. Occlusion and Motion Reasoning for Long-term Tracking. ECCV - European Conference on Computer Vision, Sep 2014, Zurich, Switzerland. pp.172-187, ⟨10.1007/978-3-319-10599-4_12⟩. ⟨hal-01020149⟩
1174 Consultations
4709 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More