Automatic eduction and statistical analysis of coherent structures in the wall region of a confine plane

This paper describes a vortex detection algorithm used to expose and statistically characterize the coherent flow patterns observable in the velocity vector fields measured by Particle Image Velocimetry (PIV) in the impingement region of air curtains. The philosophy and the architecture of this algorithm are presented. Its strengths and weaknesses are discussed. The results of a parametrical analysis performed to assess the variability of the response of our algorithm to the 3 user-specified parameters in our eduction scheme are reviewed. The technique is illustrated in the case of a plane turbulent impinging twin-jet with an opening ratio of 10. The corresponding jet Reynolds number, based on the initial mean flow velocity U0 and the jet width e, is 14000. The results of a statistical analysis of the size, shape, spatial distribution and energetic content of the coherent eddy structures detected in the impingement region of this test flow are provided. Although many questions remain open, new insights into the way these structures might form, organize and evolve are given. Relevant results provide an original picture of the plane turbulent impinging jet

Algorithms for trajectory integration in multiple views

PhDThis thesis addresses the problem of deriving a coherent and accurate localization of moving objects from partial visual information when data are generated by cameras placed in di erent view angles with respect to the scene. The framework is built around applications of scene monitoring with multiple cameras. Firstly, we demonstrate how a geometric-based solution exploits the relationships between corresponding feature points across views and improves accuracy in object location. Then, we improve the estimation of objects location with geometric transformations that account for lens distortions. Additionally, we study the integration of the partial visual information generated by each individual sensor and their combination into one single frame of observation that considers object association and data fusion. Our approach is fully image-based, only relies on 2D constructs and does not require any complex computation in 3D space. We exploit the continuity and coherence in objects' motion when crossing cameras' elds of view. Additionally, we work under the assumption of planar ground plane and wide baseline (i.e. cameras' viewpoints are far apart). The main contributions are: i) the development of a framework for distributed visual sensing that accounts for inaccuracies in the geometry of multiple views; ii) the reduction of trajectory mapping errors using a statistical-based homography estimation; iii) the integration of a polynomial method for correcting inaccuracies caused by the cameras' lens distortion; iv) a global trajectory reconstruction algorithm that associates and integrates fragments of trajectories generated by each camera

Looking through the eyes of the painter: from visual perception to non-photorealistic rendering

In this paper we present a brief overview of the processing in the primary visual cortex, the multi-scale line/edge and keypoint representations, and a model of brightness perception. This model, which is being extended from 1D to 2D, is based on a symbolic line and edge interpretation: lines are represented by scaled Gaussians and edges by scaled, Gaussian-windowed error functions. We show that this model, in combination with standard techniques from graphics, provides a very fertile basis for non-photorealistic image rendering

Models for Flow Rate Simulation in Gear Pumps: A Review

Gear pumps represent the majority of the fixed displacement machines used for flow generation in fluid power systems. In this context, the paper presents a review of the different methodologies used in the last years for the simulation of the flow rates generated by gerotor, external gear and crescent pumps. As far as the lumped parameter models are concerned, different ways of selecting the control volumes into which the pump is split are analyzed and the main governing equations are presented. The principles and the applications of distributed models from 1D to 3D are reported. A specific section is dedicated to the methods for the evaluation of the necessary geometric quantities: analytic, numerical and Computer-Aided Design (CAD)-based. The more recent studies taking into account the influence on leakages of the interactions between the fluid and the mechanical parts are explained. Finally the models for the simulation of the fluid aeration are described. The review brings to evidence the increasing effort for improving the simulation models used for the design and the optimization of the gear machines

Spatio-temporal Texture Modelling for Real-time Crowd Anomaly Detection

With the rapidly increasing demands from surveillance and security industries, crowd behaviour analysis has become one of the hotly pursued video event detection frontiers within the computer vision arena in recent years. This research has investigated innovative crowd behaviour detection approaches based on statistical crowd features extracted from video footages. In this paper, a new crowd video anomaly detection algorithm has been developed based on analysing the extracted spatio-temporal textures. The algorithm has been designed for real-time applications by deploying low-level statistical features and alleviating complicated machine learning and recognition processes. In the experiments, the system has been proven a valid solution for detecting anomaly behaviours without strong assumptions on the nature of crowds, for example, subjects and density. The developed prototype shows improved adaptability and efficiency against chosen benchmark systems