— This paper presents a robust model-based visual tracking algorithm that can give accurate 3D pose of a rigid object. Our tracking algorithm uses an incremental pose update sche...
Youngrock Yoon, Akio Kosaka, Jae Byung Park, Avina...
We describe an online approach to learn non-linear motion patterns and robust appearance models for multi-target tracking in a tracklet association framework. Unlike most previous...
— We introduce a fast and robust subspace-based approach to appearance-based object tracking. The core of our approach is based on Fast Robust Correlation (FRC), a recently propo...
Stephan Liwicki, Stefanos Zafeiriou, Georgios Tzim...
This paper presents a robust object tracking method via a spatial bias appearance model learned dynamically in video. Motivated by the attention shifting among local regions of a ...
This paper presents a Bayesian framework for multi-cue 3D object tracking of deformable objects. The proposed spatio-temporal object representation involves a set of distinct linea...