In this paper, we present a multi-modal perception based framework to realize a nonintrusive domestic assistive robotic system. It is non-intrusive in that it only starts interaction with a user when it detects the user’s intention to do so. All the robot’s actions are based on multi-modal perceptions which include user detection based on RGB-D data, user’s intention-for-interaction detection w...

Use of automatic classification for Indirect Immunofluorescence (IIF) images of HEp-2 cells is increasingly gaining interest in Antinuclear Autoantibodies (ANAs) detection. In order to improve the classification accuracy, we propose a multi-modal joint dictionary learning method, to obtain a discriminative and reconstructive dictionary while training a classifier simultaneously. Here, the term ...

In this paper we discuss a multi-modal agent platform, based on the BDI paradigm. We now have environments where more than one agent is available and where there is a need for uniformity in agent design and agent interaction. This requires a more general and uniform approach to developing agent-oriented virtual environments that allow multi-modal interaction. We first focus on a formal model fo...

This article presents a novel framework to register and fuse heterogeneous sensory data. Our approach is based on geometrically registration of sensory data onto a set of virtual parallel planes and then applying an occupancy grid for each layer. This framework is useful in surveillance applications in presence of multi-modal sensors and can be used specially in tracking and human behavior unde...

The potential advantages of behavioural biometrics are that they can be utilised in a transparent (non-intrusive) and continuous authentication system. However, individual biometric techniques are not suited to all users and scenarios. One way to increase the reliability of transparent and continuous authentication systems is create a multi-modal behavioural biometric authentication system. Thi...

ABSTRACT This paper is organized as follows. In Section 2, we formulate the proposed UMPC method for modeling nonstationary and multi-modal data. Both MPC and UPC are shown to be special cases of the proposed UMPC model. We apply UMPC to error concealment in Section 3. The experiment results in Section 4 show the performance of UMPC for error concealment over conventional methods. We then concl...

Magnetic resonance imaging (MRI) studies in early Parkinson's disease (PD) have shown promise in the detection of disease-related brain changes in the white and deep grey matter. We set out to establish whether intrinsic cortical involvement in early PD can be detected with quantitative MRI. We collected a rich, multi-modal dataset, including diffusion MRI, T1 relaxometry and cortical morphomet...

We study prefixed tableaux for first-order multi-modal logic, providing proofs for soundness and completeness theorems, a Herbrand theorem on deductions describing the use of Herbrand or Skolem terms in place of parameters in proofs, and a lifting theorem describing the use of variables and constraints to describe instantiation. The general development applies uniformly across a range of regime...

Multi-modal transportation is a logistics problem in which a set of goods have to be transported to different places, with the combination of at least two modes of transport, without a change of container for the goods. The goal of this paper is to describe TIMIPLAN, a system that solves multi-modal transportation problems in the context of a project for a big company. In this paper, we combine...

Traffic simulations need to include other modes of transportation besides car. This paper explains how this can be implemented in a large scale micro-simulation package. The most important element is to recognize that trips start and end on the walk network, and to explicitely model this mode.