We present an existence and stability theory for gravity–capillary solitary waves on the top surface of and interface between two perfect fluids of different densities, the lower one being of infinite depth. Exploiting a classical variational principle, we prove the existence of a minimiser of the wave energy E subject to the constraint I= 2 μ, where I is the wave momentum and 0 < μ< μ, where μ is

This study conducts an investigation and feasibility study on different Reynolds numbers (6000–12000) and Rotation numbers (0.05–0.25) in a matrix cooling geometry. An intended geometry that can be used in gas turbine blades is provided based on flow and heat transfer performance given in these Reynolds and rotation number ranges for stationary and rotational state and then compared with experimen

In this study, molecular properties of wheat starch from three different types of breads were analyzed using asymmetric flow field-flow (AF4) connected to multi-angle light scattering (MALS) and differential refractive index (dRI) detectors. This analysis allowed the determination of molecular properties, i.e. molar mass (M), root-mean-square radius (rrms), apparent density (ρapp) and conformation

The Port of Rotterdam is an important industrial cluster, comprising mainly oil refining, chemical production and power generation. In 2016, the port's industry accounted for 19% of the Netherlands’ total CO2 emissions. The Port of Rotterdam Authority is aware that the cluster is heavily exposed to future decarbonisation policies, as most of its activities focus on trading, handling, converting an

Hidden Markov models have been extensively and successfully used for the recognition of human actions. Though there exist wellestablished algorithms to optimize the transition and output probabilities, the type of features to use and specifically the number of states and Gaussian have to be chosen manually. Here we present a quantitative study on selecting the optimal feature set for recognition o

Tracking of rigid and articulated objects is usually addressed within a particle filter framework or by correspondence based gradient descent methods. We combine both methods, such that (a) the correspondence based estimation gains the advantage of the particle filter and becomes able to follow multiple hypotheses while (b) the particle filter becomes able to propagate the particles in a better ma

In this work1 a combination of depth and silhouette information is presented to track the motion of a human from a single view. Depth data is acquired from a Photonic Mixer Device (PMD), which measures the time-of-flight of light. Correspondences between the silhouette of the projected model and the real image are established in a novel way, that can handle cluttered non-static backgrounds. Pose i

There is biological evidence that human actions are composed out of action primitives, like words and sentences being composed out of phonemes. Similarly to language processing, one possibility to model and recognize complex actions is to use grammars with action primitives as the alphabet. A major challenge here is that the action primitives need to be recovered first from the noisy input signal

In this paper, we analyze the different approaches taken to date within the computer vision, robotics and artificial intelligence communities for the representation, recognition, synthesis and understanding of action. We deal with action at different levels of complexity and provide the reader with the necessary related literature references. We put the literature references further into context a

The ability to integrate information over time in order to come to a conclusion is a strength of cognitive systems. It allows the system, e.g., to1verify insecure observations: This is the case when data is noisy or of low-quality, or if conditions in general are non-optimal. 2exploit general knowledge about spatio-temporal relations: This allows the system to exploit the specific dynamics of an o

There is biological evidence that human actions are composed out of action primitives, similarly to words and sentences being composed out of phonemes. Given a set of action primitives and an action composed out of these primitives we present a Hidden Markov Model-based approach that allows to recover the action primitives in that action. In our approach, the primitives may have different lengths,

This survey reviews advances in human motion capture and analysis from 2000 to 2006, following a previous survey of papers up to 2000 [T.B. Moeslund, E. Granum, A survey of computer vision-based human motion capture, Computer Vision and Image Understanding, 81(3) (2001) 231-268.]. Human motion capture continues to be an increasingly active research area in computer vision with over 350 publication

In this paper we introduce a model-based background subtraction approach where first silhouettes, which model the correlations between neightboring pixels are being learned and where then Bayesian propagation over time is used to select the proper silhouette model and tracking parameters. Bayes propagation is attractive in our application as it allows to deal with uncertainties in the video data d

We propose a view-based approach to recognize humans from their gait. Two different image features have been considered: The width of the outer contour of the binarized silhouette of the walking person and the entire binary silhouette itself. To obtain the observation vector from the image features, we employ two different methods. In the first method, referred to as the indirect approach, the hig

In this article, we present a new method for visual face tracking that is carried out in a wavelet subspace. Initially, a wavelet representation for the face template is created, which spans a low-dimensional subspace of the image space. The video sequence frames, where the face is tracked, are then orthogonally projected into this subspace. This can be done efficiently through a small number of a

Recognition of human faces using a gallery of still or video images and a probe set of videos is systematically investigated using a probabilistic framework. In still-to-video recognition, where the gallery consists of still images, a time series state space model is proposed to fuse temporal information in a probe video, which simultaneously characterizes the kinematics and identity using a motio

A new exemplar-based probabilistic approach for face recognition in video sequences is presented. The approach has two stages: First, Exemplars, which are selected representatives from the raw video, are automatically extracted from gallery videos. The exemplars are used to summarize the gallery video information. In the second part, exemplars are then used as centers for probabilistic mixture dis

We present a technique for facial feature localization using a two-level hierarchical wavelet network. The first level wavelet network is used for face matching, and yields an affine transformation used for a rough approximation of feature locations. Second level wavelet networks for each feature are then used to fine-tune the feature locations. Construction of a training database containing hiera