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In this paper absolute dispersion of GPS-equipped drifters of the MREA14 campaign in the Mar Grande Basin of Taranto was investigated. Velocity variance and integral time scale were computed. Different procedures to infer the mean velocity from drifter data were examined. A comparison within experimental and theoretical values of the displacement variance is introduced pointing out limits and requirements...
In this paper we present a neurally plausible model of human infant reaching that is based on embodied artificial intelligence, which emphasizes the importance of the sensorimotor interaction of an agent and the world. This model encompasses both learning sensorimotor correlations through motor babbling and also arm motion planning using spreading activation. This model is organized in three layers...
This paper proposes a method for learning pedestrian dynamics with kriging, which is a spatial interpolation method in geosciences. Pedestrian dynamics is generally restricted by other pedestrians and its restriction is caused by social interaction between them. In the proposed method, the social interaction is represented by spatio-temporal correlation of pedestrian dynamics and the correlation is...
The bag-of-visual-words model has been widely utilized for content based image and video retrieval due to its scalability. In this paper, we extend this model for human action video retrieval. We adopt dense trajectory features which are able to achieve the state-of-the-art performance on action recognition, while most of the existing video retrieval methods utilize descriptors of local interest points...
To deal with redundancy and high-dimensionality that are typical of movement data, we propose to decompose action matrices in two decoupled steps: first, we discover a set of key postures, that is, vectors corresponding to key relationships among degrees of freedom (like angles between body parts) which we call spatial basis (SB) and second, we impose a parametric model to the spatio-temporal (ST)...
While hand trajectory has been successfully modeled for single arm reaching movement, few works have considered the bimanual reaching movement and no study has modeled the dyadic reaching movement. In a bimanual task, both hands belong to the same person, while in a dyadic task each hand belongs to a different person. In this paper, we study both bimanual and dyadic reaching movements and show that...
In this presentation, we describe how field-field correlation functions may be efficiently propagated using ideas based on ray propagation. The key point is to make a connection between the field-field correlation function and the corresponding Wigner function, which is obtained from it by Fourier transformation.
This paper considers the detection of ball in a basketball game covered by multiple loosely synchronized cameras. First, plausible ball candidates are detected on the nodes of a 3D grid defined around the basket. This is done by correlating independently in each view the spatial template of the ball with a precomputed foreground mask. Efficient implementation of this step relies on integral images...
In this paper, we consider the tracking of mobile terminals based on the received signal strength (RSS) measured from several base stations. The spatial correlation of the random shadowing is exploited in order to improve the position tracking. We define an auto-regressive (AR) model of the temporal evolution of the shadowing. This model allows for performing a joint tracking of the position and the...
Out-of-equilibrium price dynamics are studied using agent-based computational models. We examine how agents with bounded rationality act in an environment in which they do not know precisely both relative prices and the level of the prices. We model imprecision and uncertainty with fuzzy numbers and use the theory of probabilistic sets as part of the simulation model. Our results explain both positive...
Today, the necessity of faster and smaller devices is pushing the electronic industry into developing electron devices with solid-state structures of few nanometers. In these dimensions electron dynamics are in general governed by quantum mechanical laws. We have recently shown that Bohmian trajectories allow a direct treatment of the many-particle interaction among electrons with an accuracy comparable...
We present a novel method for learning pedestrian trajectories which is able to describe complex motion patterns such as multiple crossing paths. This approach adopts Kernel Canonical Correlation Analysis (KCCA) to build a mapping between the physical location space and the trajectory patterns space. To model crossing paths we rely on a clustering algorithm based on Kernel K-means with a Dynamic Time...
Scene recognition in an unconstrained setting is an open and challenging problem with wide applications. In this paper, we study the role of scene dynamics for improved representation of scenes. We subsequently propose dynamic attributes which can be augmented with spatial attributes of a scene for semantically meaningful categorization of dynamic scenes. We further explore accurate and generalizable...
Video synchronization is one of the first steps in most of the multi-camera systems. In this paper we introduce a novel, computationally simple and reliable approach for video synchronization that does not require any pre-computed camera geometries or tracking certain features. We define a feature called center of motion (COM) and obtain its trajectories along the temporal axis for both videos. Then...
In this paper we propose a new model to generate handwriting based on behavioral patterns we believe is to be found in humans when imitating a written character. The proposed algorithm has a hierarchical structure. It is consisted of two main levels. At the first level the graphical features of the written letter to be imitated are extracted. These features are the directions of movement for each...
With great potential in studying neuro-development, neuro-degeneration, and the aging process, longitudinal image data is gaining increasing interest and attention in the neuroimaging community. In this paper, we present a parametric nonlinear model to statistically study multivariate longitudinal data with asymptotic properties. We demonstrate our preliminary results in a combined study of two longitudinal...
The phenomenon of roundoff-error propagation is a well known problem in computations involving floating point arithmetic. Prominent works in the field of error analysis include (1) the error-analysis based on differential error-propagation model for computer algebra system (CAS), (2) the identification and reformulation of instability in a code generated by CAS, (3) estimating the bounds on errors...
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