This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
This paper presents a new approach to multiple objects tracking that combines particle filters and k-means. The approach has been tested under an important real world situation, ...
Tracking moving obstacles from a moving platform is a useful skill for the coming generation of mobile robot. The methods used in existing moving objects tracking that operated fr...
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 ...
The aim of this work is to investigate how to exploit the temporal information in a video sequence for the task of face recognition. Following the approach in [11], we propose a p...