Step-by-Step Description of Lateral Interaction in Accumulative Computation

Abstract. In this paper we present a method for moving objects detection and labeling denominated Lateral Interaction in Accumulative Computation (LIAC). The LIAC method usefulness in the general task of motion detection may be appreciated by means of some step-by-step descriptions of significant examples of object detection in video sequences of synthetic and real images

Step-by-step description of lateral interaction in accumulative computation

In this paper we present a method for moving objects detection and labeling denominated Lateral Interaction in Accumulative Computation (LIAC). The LIAC method usefulness in the general task of motion detection may be appreciated by means of some step-by-step descriptions of significant examples of object detection in video sequences of synthetic and real images

Modelling the stereovision-correspondence-analysis task by lateral inhibition in accumulative computation problem-solving method.

Recently, the Algorithmic Lateral Inhibition (ALI) method and the Accumulative Computation (AC) method have proven to be efficient in modelling at the knowledge level for general-motion-detection tasks in video sequences. More precisely, the task of persistent motion detection has been widely expressed by means of the AC method, whereas the ALI method has been used with the objective of moving objects detection, labelling and further tracking. This paper exploits the current knowledge of our research team on the mentioned problem-solving methods to model the Stereovision-Correspondence-Analysis (SCA) task. For this purpose, ALI and AC methods are combined into the Lateral Inhibition in Accumulative Computation (LIAC) method. The four basic subtasks, namely ?LIAC 2D Charge-Memory Calculation?, ?LIAC 2D Charge-Disparity Analysis? and ?LIAC 3D Charge-Memory Calculation? in our proposal of SCA are described in detail by inferential CommonKADS schemes. It is shown that the LIAC method may perfectly be used to solve a complex task based on motion information inherent to binocular video sequences

Revisiting algorithmic lateral inhibition and accumulative computation

Certainly, one of the prominent ideas of Professor Mira was that it is absolutely mandatory to specify the mechanisms and/or processes underlying each task and inference mentioned in an architecture in order to make operational that architecture. The conjecture of the last fifteen years of joint research of Professor Mira and our team at University of Castilla-La Mancha has been that any bottom-up organization may be made operational using two biologically inspired methods called ?algorithmic lateral inhibition?, a generalization of lateral inhibition anatomical circuits, and ?accumulative computation?, a working memory related to the temporal evolution of the membrane potential. This paper is dedicated to the computational formulations of both methods, which have led to quite efficient solutions of problems related to motion-based computer vision

A historical perspective of algorithmic lateral inhibition and accumulative computation in computer vision

Certainly, one of the prominent ideas of Professor José Mira was that it is absolutely mandatory to specify the mechanisms and/or processes underlying each task and inference mentioned in an architecture in order to make operational that architecture. The conjecture of the last fifteen years of joint research has been that any bottom-up organization may be made operational using two biologically inspired methods called ?algorithmic lateral inhibition?, a generalization of lateral inhibition anatomical circuits, and ?accumulative computation?, a working memory related to the temporal evolution of the membrane potential. This paper is dedicated to the computational formulation of both methods. Finally, all of the works of our group related to this methodological approximation are mentioned and summarized, showing that all of them support the validity of this approximation

Towards a digital twin for prediction of rail damage evolution in railway curves

Railway maintenance incurs significant expenses, and reducing the costs while maintaining safety levels and functionality is of great industrial and societal interest. Accurately predicting rail damage is crucial for cost-effective maintenance and extending rail life. This thesis focuses on developing a digital twin that can predict the rail damage evolution in a curved track under operational traffic, considering plastic deformation, wear, and surface Rolling Contact Fatigue (RCF) by accurate and fast simulations.The first part of the thesis contains results from long-term simulations of rail damage for a given traffic scenario. The adopted simulation methodology is calibrated and validated using field tests. The numerical methodology in Paper A employs a framework that incorporates multiple steps that are applied iteratively to predict rail head degradation. The different steps are (1) the dynamic vehicle-track interaction for a given load sequence, (2) elastic-plastic wheel-rail contact, (3) accumulative rail damage due to cyclic plasticity, wear, and surface RCF, and (4) rail profile update from the accumulated wear and plasticity. Thereafter, the simulation steps can be repeated. It is demonstrated how the numerical model can be calibrated to match field measurements of the averaged geometry changes of the rail cross-section and predict surface RCF crack initiation. To allow for better predictions of the local wear distribution on the rail head, a model sensitivity study is performed in Paper B to determine the most significant model parameters for vehicle and track. Also, the effect of different contact modeling approaches is investigated. By including a freight vehicle, using different measured wheel profile samples in the load sequence, and considering a different contact modeling approach, promising predictions of the wear distribution are obtained.Furthermore, a reduced-order model based on Proper Generalized Decomposition (PGD) is developed in Paper C for accurately simulating the deformation in the rail under varying contact loads. It enables cost-efficient simulations required for the digital twin framework. As a first step towards replacing computationally demanding nonlinear finite element simulations for the plastic deformation evaluation, the current version of the PGD model involves a domain decomposition of a three-dimensional elastic rail head combined with a parameterized discrete load to account for different load scenarios in an automated fashion. It is shown that the three-dimensional PGD model can be computed with two-dimensional complexity and can generate the parametrized displacement field for various loading scenarios

Modelling Pluvial Flooding in Urban Areas Coupling the Models Iber and SWMM

[Abstract] Dual urban drainage models allow users to simulate pluvial urban flooding by analysing the interaction between the sewer network (minor drainage system) and the overland flow (major drainage system). This work presents a free distribution dual drainage model linking the models Iber and Storm Water Management Model (SWMM), which are a 2D overland flow model and a 1D sewer network model, respectively. The linking methodology consists in a step by step calling process from Iber to a Dynamic-link Library (DLL) that contains the functions in which the SWMM code is split. The work involves the validation of the model in a simplified urban street, in a full-scale urban drainage physical model and in a real urban settlement. The three study cases have been carefully chosen to show and validate the main capabilities of the model. Therefore, the model is developed as a tool that considers the main hydrological and hydraulic processes during a rainfall event in an urban basin, allowing the user to plan, evaluate and design new or existing urban drainage systems in a realistic way.Xunta de Galicia; EAPA_45/201

Real-time motion detection by lateral inhibition in accumulative computation.

Many researchers have explored the relationship between recurrent neural networks and finite state machines. Finite state machines constitute the best characterized computational model, whereas artificial neural networks have become a very successful tool for modeling and problem solving. In the few last years, the neurally inspired lateral inhibition in accumulative computation (LIAC) method and its application to the motion detection task have been introduced. The article shows how to implement the tasks directly related to LIAC in motion detection by means of a formal model described as finite state machines. This paper introduces two steps towards that direction: (a) A simplification of the general LIAC method is performed by formally transforming it into a finite state machine. (b) A hardware implementation of such a designed LIAC module, as well as an 8×8 LIAC module, has been tested on several video sequences, providing promising performance results

Lateral interaction in accumulative computation

To be able to understand the motion of non-rigid objects, techniques in image processing and computer vision are essential for motion analysis. Lateral interaction in accumulative computation for extracting non-rigid blobs and shapes from an image sequence has recently been presented, as well as its application to segmentation from motion. In this paper we show an architecture consisting of five layers based on spatial and temporal coherence in visual motion analysis with application to visual surveillance. The LIAC method used in general task ?spatio-temporal coherent shape building? consists in (a) spatial coherence for brightness-based image segmentation, (b) temporal coherence for motion-based pixel charge computation, (c) spatial coherence for charge-based pixel charge computation, (d) spatial coherence for charge-based blob fusion, and, (e) spatial coherence for charge-based shape fusion. In our case, temporal coherence (in accumulative computation) is understood as a measure of frame to frame motion persistency on a pixel, whilst spatial coherence (in lateral interaction) is a measure of pixel to neighbouring pixels accumulative charge comparison

Multi-physic system simplification method applied to a helicopter flight axis active control

A helicopter flight axis control, which is a complex multi-physic system, is modelled using an energetic based graphical tool: the Energetic Macroscopic Representation. Elements of the system are mainly composed of passive technologies and their number tends to increase year after year to improve the pilots comfort by adding new functions. A new methodology is proposed to transform the system into a new active one by replacing some hydro-mechanical elements by a new controllable active mechanical source. The challenge is to simplify the flight control architecture while preserving the global behaviour of the system