Particle filters provide a robust framework for nonlinear and non-Gaussian estimation problems. In this paper, we present a method to incorporate dominant modulation-domain (Ampl...
Robust visual tracking has become an important topic in the field of computer vision. The integration of cues such as color, edge strength and motion has proved to be a promising ...
Chunhua Shen, Anton van den Hengel, Anthony R. Dic...
In this paper, a dynamic multi-modal fusion scheme for tracking multiple targets with Monte-Carlo filters is presented, with the goal of achieving robustness by combining complime...
A new particle filter, Kernel Particle Filter (KPF), is proposed for visual tracking for multiple objects in image sequences. The KPF invokes kernels to form a continuous estimate...
A novel particle filter, the Memory-based Particle Filter
(M-PF), is proposed that can visually track moving objects
that have complex dynamics. We aim to realize robustness
aga...
Dan Mikami (NTT), Kazuhiro Otsuka (NTT), Junji YAM...