no code implementations • 12 Jul 2021 • Giorgos Karvounas, Nikolaos Kyriazis, Iason Oikonomidis, Aggeliki Tsoli, Antonis A. Argyros
The amount and quality of datasets and tools available in the research field of hand pose and shape estimation act as evidence to the significant progress that has been made. However, even the datasets of the highest quality, reported to date, have shortcomings in annotation.
no code implementations • ECCV 2018 • Aggeliki Tsoli, Antonis A. Argyros
We present a novel method that is able to track a complex deformable object in interaction with a hand.
no code implementations • CVPR 2017 • Konstantinos Papoutsakis, Costas Panagiotakis, Antonis A. Argyros
We treat this type of temporal action co-segmentation as a stochastic optimization problem that is solved by employing Particle Swarm Optimization (PSO).
no code implementations • 27 Oct 2015 • Georg Poier, Konstantinos Roditakis, Samuel Schulter, Damien Michel, Horst Bischof, Antonis A. Argyros
Model-based approaches to 3D hand tracking have been shown to perform well in a wide range of scenarios.
no code implementations • CVPR 2015 • Tu-Hoa Pham, Abderrahmane Kheddar, Ammar Qammaz, Antonis A. Argyros
We present a novel, non-intrusive approach for estimating contact forces during hand-object interactions relying solely on visual input provided by a single RGB-D camera.
no code implementations • CVPR 2014 • Iason Oikonomidis, Manolis I.A. Lourakis, Antonis A. Argyros
The method has been tested for the problems of tracking the articulation of a single hand (27D parameter space) and two hands (54D space).