Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
We devise and experiment with a dynamical kernel-based system for tracking hand movements from neural activity. The state of the system corresponds to the hand location, velocity,...
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
We introduce linear methods for model-based tracking of nonrigid 3D objects and for acquiring such models from video. 3D motions and flexions are calculated directly from image in...
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...