Abstmct-In this correspondence, we show how to recover the motion of an observer relative to a planar surface from image brightness derivatives. We do not compute the optical flow as an intermediate step, only the spatial and temporal brightness gradients (at a minimum of eight points). We first present two iterative schemes for solving nine nonlinear equations in terms of the motion and surface parameters that are derived from a least-squares fomulation. An initial pass over the relevant image region is wed to accumulate a number of moments of the image brightness derivatives. All of the quantities used in the iteration are efficiently computed from these totals without the need to refer back to the image. We then show that either of two possible solutions can be obtained in closed form. We first solve a linear matrix equation for the elements of a 3 x 3 matrix. The eigenvalue decomposition of the symmetric part of the matrix is then used to compute the motion parameters and the plane orientation. A new compact notation allows us to show easily that there are at most two planar solutions.

IEEE Transactions on Pattern Analysis and Machine Intelligence

We survey the research on interactive evolutionary computation (IEC). The IEC is an EC that optimizes systems based on subjective human evaluation. The definition and features of the IEC are first described and then followed by an overview of the IEC research. The overview primarily consists of application research and interface research. In this survey the IEC application fields include graphic arts and animation, 3D computer graphics lighting, music, editorial design, industrial design, facial image generation, speed processing and synthesis, hearing aid fitting, virtual reality, media database retrieval, data mining, image processing, control and robotics, food industry, geophysics, education, entertainment, social system, and so on. The interface research to reduce human fatigue is also included. Finally, we discuss the IEC from the point of the future research direction of computational intelligence. This paper features a survey of about 250 IEC research papers.

/pdf/interactive-evolutionary-computation-fusion-of-the-1a83gb7c9d.pdf

Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation

Technology developments in structural health monitoring of large-scale bridges

Most current Artificial Neural Network (ANN) models are based on highly simplified brain dynamics. They have been used as powerful computational tools to solve complex pattern recognition, function estimation, and classification problems. ANNs have been evolving towards more powerful and more biologically realistic models. In the past decade, Spiking Neural Networks (SNNs) have been developed which comprise of spiking neurons. Information transfer in these neurons mimics the information transfer in biological neurons, i.e., via the precise timing of spikes or a sequence of spikes. To facilitate learning in such networks, new learning algorithms based on varying degrees of biological plausibility have also been developed recently. Addition of the temporal dimension for information encoding in SNNs yields new insight into the dynamics of the human brain and could result in compact representations of large neural networks. As such, SNNs have great potential for solving complicated time-dependent pattern recognition problems because of their inherent dynamic representation. This article presents a state-of-the-art review of the development of spiking neurons and SNNs, and provides insight into their evolution as the third generation neural networks.

Spiking neural networks.

In the field of transportation, data analysis is probably the most important and widely used research tool available. In the data analysis universe, there are two ‘schools of thought’; the first uses statistics as the tool of choice, while the second – one of the many methods from – Computational Intelligence. Although the goal of both approaches is the same, the two have kept each other at arm’s length. Researchers frequently fail to communicate and even understand each other’s work. In this paper, we discuss differences and similarities between these two approaches, we review relevant literature and attempt to provide a set of insights for selecting the appropriate approach.

Statistical methods versus neural networks in transportation research: Differences, similarities and some insights

In order to establish a rational bridge management program, it is necessary to develop a cost-effective decision-support system for the maintenance of bridges. In this paper, an attempt is made to develop a bridge management system that can provide practical maintenance plans by using an improved multi-objective genetic algorithm. A group of bridges is analyzed to demonstrate the applicability and efficiency of the proposed method.

Optimal bridge maintenance planning using improved multi-objective genetic algorithm

This book comprises most of the papers presented at the First US/Japan Workshop on Life-Cycle Cost Analysis and Design of Civil Infrastructure Systems, held in Honolulu, Hawaii, August 7-8, 2000, and several invited contributions, mostly from Europe. The 18 papers cover a wide range of studies on life-cycle cost analysis, design, maintenance and management of civil infrastructure systems. Contributions are from a range of internationally recognized researchers and practicing structural engineers from the United States, Japan, and Europe. Topics include: conceptual design of structural systems; time-variant reliability of structures; structural health monitoring and symptom-based reliability; monitoring and testing for fatigue prediction; lifetime reliability profiles for fatigue and corrosion; maintenance planning for road pavements and structures; maintenance planning of reinforced concrete decks; bridge management systems; optimized and conventional bridges; optimal planning of maintenance and inspection; life-cycle cost assessment for bridge maintenance; specifications to aid life-cycle cost analyses; maintenance cost of deteriorating civil infrastructures; probabilistic models of cost for management of existing structures; and user cost and its applications to bridge management systems. This book will be invaluable to all concerned with life-cycle costing of civil infrastructure systems.

Life-cycle cost analysis and design of civil infrastructure systems

This paper will discuss the relationships among the minimization of Life-Cycle Cost (LCC), the optimal extension of structural service life, and the target safety level by using the multi-objective genetic algorithm. The paper confirms that LLC, service life and durability level have a trade-off relation and the multi-objective genetic algorithm proved to be a useful tool in finding an optimal maintenance plan.

Life-Cycle Cost Analysis for Infrastructure Systems: Life-Cycle Cost vs. Safety Level vs. Service Life

The International Association for Life-Cycle Civil Engineering (IALCCE) was founded in 2006 to support this challenge and to create a fertile ground for promoting the study, research, and applicati...

Life-cycle of structural systems: design, assessment, maintenance and management

The life-cycle cost (LCC) concepts and methods have impacted remarkably on the field of civil infrastructure. In this paper, LCC design concepts and methods are discussed with emphasis on bridges and road networks. The relationships among several performance measures are discussed. An attempt is made to provide rational balances of these measures by using a multi-objective genetic algorithm. Furthermore, LCC is evaluated focusing on the effects of earthquakes. At first, LCC analysis is formulated to consider the socio-economic effects due to the collapse of structures as well as the minimisation of lifetime maintenance cost. A stochastic model of structural response under earthquake effects is proposed. Then, the probability of failure of an individual bridge due to the earthquake excitation is calculated based on the reliability theory. In addition, LCC evaluations are performed not only for a single bridge but also for groups of bridges forming road networks.

Life-cycle Cost of Civil Infrastructure With Emphasis on Balancing Structural Performance and Seismic Risk of Road Network

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