Optimal Importance Sampling for Tracking in Image Sequences: Application to Point Tracking

Abstract. In this paper, we propose a particle filtering approach for tracking applications in image sequences. The system we propose combines a measurement equation and a dynamic equation which both depend on the image sequence. Taking into account several possible observations, the likelihood is modeled as a linear combination of Gaussian laws. Such a model allows inferring an analytic expression of the optimal importance function used in the diffusion process of the particle filter. It also enables building a relevant approximation of a validation gate. We demonstrate the significance of this model for a point tracking application.

• Type: Conference
• Year: 2004
• Where: ECCV
• Authors: Étienne Mémin, Elise Arnaud
• Keywords: Computer Vision, Dynamic Equation, ECCV 2004, Measurement Equation, Optimal Importance Function, Particle Filtering Approach, Point Tracking Application