3D tracking based on possibilities rather than probabilities

Guillaume Chiron (1) , Petra Gomez-Krämer (1) , Michel Ménard (1)

1 L3I - Laboratoire Informatique, Image et Interaction - EA 2118

We propose in this paper a method to constraint the tracking to the physically possible space without knowledge of the scene. The idea is to use a naively made trajectory dataset as a base to track the targets into the possible space rather than the probable space. First, a trajectory database is computed under weak assumptions permissive classic Kalman Filter). Then, for the effective tracking, we replace the prediction phase of the KF to rely only on the dynamic stored in the database of historical trajectories. We show that performances can reach these obtained by other methods based on strong assumptions (e.g. the 3D model of the scene).

Mots clés: 3D tracking; Honeybees monitoring; Scene constraints; Trajectory database; Colony dynamics

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

Guillaume Chiron, Petra Gomez-Krämer, Michel Ménard. 3D tracking based on possibilities rather than probabilities. VAIB - Workshop on Visual observation and analysis of Vertebrate And Insect Behavior, in conjunction of ICPR, Aug 2014, Sweden. pp.9. ⟨hal-01061999⟩