We explore an approach to 3D people tracking with learned motion models and deterministic optimization. The tracking problem is formulated as the minimization of a differentiable ...
This paper proposes a method for capturing the performance
of a human or an animal from a multi-view video
sequence. Given an articulated template model and silhouettes
from a m...
Juergen Gall (BIWI, ETH Zurich), Carsten Stoll (Ma...
This paper proposes a model-based methodology for recognizing and tracking objects in digital image sequences. Objects are represented by attributed relational graphs (or ARGs), w...
Ana Beatriz V. Graciano, Roberto Marcondes Cesar J...
Abstract— Recently, classical pairwise Structure From Motion (SfM) techniques have been combined with non-linear global optimization (Bundle Adjustment, BA) over a sliding window...
Javier Civera, Oscar G. Grasa, Andrew J. Davison, ...
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...