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105
An iterative image registration technique with an application to stereo vision
 In IJCAI81
, 1981
"... Image registration finds a variety of applications in computer vision. Unfortunately, traditional image registration techniques tend to be costly. We present a new image registration technique that makes use of the spatial intensity gradient of the images to find a good match using a type of Newton ..."
Abstract

Cited by 1970 (33 self)
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Image registration finds a variety of applications in computer vision. Unfortunately, traditional image registration techniques tend to be costly. We present a new image registration technique that makes use of the spatial intensity gradient of the images to find a good match using a type of NewtonRaphson iteration. Our technique is faster because it examines far fewer potential matches between the images than existing techniques. Furthermore, this registration technique can be generalized to handle rotation, scaling and shearing. We show show our technique can be adapted for use in a stereo vision system. 2. The registration problem The translational image registration problem can be characterized as follows: We are given functions F(x) and G(x) which give the respective pixel values at each location x in two images, where x is a vector. We wish to find the disparity vector h which minimizes some measure of the difference between F(x + h) and G(x), for x in some region of interest R. (See figure 1). 1.
An Implicit Enumeration Algorithm to Generate Tests for Combinational Logic Circuits
 IEEE Transactions on Computers
, 1981
"... The DAlgorithm (DALG) is shown to be ineffective for the class of combinational logic circuits that is used to implement Error Correction and Translation (ECAT) functions. PODEM (PathOriented Decision Making) is a new test generation algorithm for combinational logic circuits. PODEM uses an implic ..."
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Cited by 219 (0 self)
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The DAlgorithm (DALG) is shown to be ineffective for the class of combinational logic circuits that is used to implement Error Correction and Translation (ECAT) functions. PODEM (PathOriented Decision Making) is a new test generation algorithm for combinational logic circuits. PODEM uses an implicit enumeration approach analogous to that used for solving 0 1 integer programming problems. It is shown that PODEM is very efficient for ECAT circuits and is significantly more efficient than DALC over the general spectrum of combinational logic circuits. A distinctive feature of PODEM is its simplicity when compared to the DAlgorithm. PODEM is a complete algorithm in that it will generate a test if one exists. Heuristics are used to achieve an efficient implicit search of the space of all possible primary input patterns until either a test is found or the space is exhausted.
GoalOriented Requirements Engineering: A Guided Tour
, 2001
"... Goals capture, at different levels of abstraction, the various objectives the system under consideration should achieve. ..."
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Cited by 192 (3 self)
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Goals capture, at different levels of abstraction, the various objectives the system under consideration should achieve.
Generalized bestfirst search strategies and the optimality of A*
 JOURNAL OF THE ACM
, 1985
"... This paper reports several properties of heuristic bestfirst search strategies whose scoring functions f depend on all the information available from each candidate path, not merely on the current cost g and the estimated completion cost h. It is shown that several known properties of A * retain t ..."
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Cited by 161 (12 self)
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This paper reports several properties of heuristic bestfirst search strategies whose scoring functions f depend on all the information available from each candidate path, not merely on the current cost g and the estimated completion cost h. It is shown that several known properties of A * retain their form (with the minmax offplaying the role of the optimal cost), which helps establish general tests of admissibility and general conditions for node expansion for these strategies. On the basis of this framework the computational optimality of A*, in the sense of never expanding a node that can be skipped by some other algorithm having access to the same heuristic information that A* uses, is examined. A hierarchy of four optimality types is defined and three classes of algorithms and four domains of problem instances are considered. Computational performances relative to these algorithms and domains are appraised. For each classdomain combination, we then identify the strongest type of optimality that exists and the algorithm for achieving it. The main results of this paper relate to the class of algorithms that, like A*, return optimal solutions (i.e., admissible) when all cost estimates are optimistic (i.e., h 5 h*). On this class, A * is shown to be not optimal and it is also shown that no optimal algorithm exists, but if the performance tests are confirmed to cases in which the estimates are also consistent, then A * is indeed optimal. Additionally, A * is also shown to be optimal over a subset of the latter class containing all bestfirst algorithms that are guided by pathdependent evaluation functions.
LAO*: A heuristic search algorithm that finds solutions with loops
, 2001
"... Classic heuristic search algorithms can find solutions that take the form of a simple path (A*), a tree, or an acyclic graph (AO*). In this paper, we describe a novel generalization of heuristic search, called LAO*, that can find solutions with loops. We show that LAO* can be used to solve Markov de ..."
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Cited by 143 (14 self)
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Classic heuristic search algorithms can find solutions that take the form of a simple path (A*), a tree, or an acyclic graph (AO*). In this paper, we describe a novel generalization of heuristic search, called LAO*, that can find solutions with loops. We show that LAO* can be used to solve Markov decision problems and that it shares the advantage heuristic search has over dynamic programming for other classes of problems. Given a start state, it can find an optimal solution without evaluating the entire state space. 2001 Elsevier Science B.V. All rights reserved. Keywords: Heuristic search; Dynamic programming; Markov decision problems 1.
Formal Refinement Patterns for GoalDriven Requirements Elaboration
, 1996
"... Abstract. Requirements engineering is concerned with the identification of highlevel goals to be achieved by the system envisioned, the refinement of such goals, the operationalization of goals into services and constraints, and the assignment of responsibilities for the resulting requirements to a ..."
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Cited by 126 (5 self)
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Abstract. Requirements engineering is concerned with the identification of highlevel goals to be achieved by the system envisioned, the refinement of such goals, the operationalization of goals into services and constraints, and the assignment of responsibilities for the resulting requirements to agents such as humans, devices and programs. Goal refinement and operationalization is a complex process which is not well supported by current requirements engineering technology. Ideally some form of formal support should be provided, but formal methods are difficult and costly to apply at this stage. This paper presents an approach to goal refinement and operationalization which is aimed at providing constructive formal support while hiding the underlying mathematics. The principle is to reuse generic refinement patterns from a library structured according to strengthening/weakening relationships among patterns. The patterns are once for all proved correct and complete. They can be used for guiding the refinement process or for pointing out missing elements in a refinement. The cost inherent to the use of a formal method is thus reduced significantly. Tactics are proposed to the requirements engineer for grounding pattern selection on semantic criteria. The approach is discussed in the context of the multiparadigm language used in the KAOS method; this language has an external semantic net layer for capturing goals, constraints, agents, objects and actions together with their links, and an inner formal assertion layer that includes a realtime temporal logic for the specification of goals and constraints. Some frequent refinement patterns are highlighted and illustrated through a variety of examples. The general principle is somewhat similar in spirit to the increasingly popular idea of design patterns, although it is grounded on a formal framework here. Keywords: Goaldriven requirements engineering, refinement,
Requirements Engineering in the Year 00: A Research Perspective
, 2000
"... Requirements engineering (RE) is concerned with the identification of the goals to be achieved by the envisioned system, the operationalization of such goals into services and constraints, and the assignment of responsibilities for the resulting requirements to agents such as humans, devices, a ..."
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Cited by 119 (11 self)
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Requirements engineering (RE) is concerned with the identification of the goals to be achieved by the envisioned system, the operationalization of such goals into services and constraints, and the assignment of responsibilities for the resulting requirements to agents such as humans, devices, and software. The processes involved in RE include domain analysis, elicitation, specification, assessment, negotiation, documentation, and evolution. Getting highquality requirements is difficult and critical. Recent surveys have confirmed the growing recognition of RE as an area of utmost importance in software engineering research and practice. The paper presents a brief history of the main concepts and techniques developed to date to support the RE task, with a special focus on modeling as a common denominator to all RE processes. The initial description of a complex safetycritical system is used to illustrate a number of current research trends in REspecific areas such as go...
Markovian Models for Sequential Data
, 1996
"... Hidden Markov Models (HMMs) are statistical models of sequential data that have been used successfully in many machine learning applications, especially for speech recognition. Furthermore, in the last few years, many new and promising probabilistic models related to HMMs have been proposed. We firs ..."
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Cited by 84 (2 self)
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Hidden Markov Models (HMMs) are statistical models of sequential data that have been used successfully in many machine learning applications, especially for speech recognition. Furthermore, in the last few years, many new and promising probabilistic models related to HMMs have been proposed. We first summarize the basics of HMMs, and then review several recent related learning algorithms and extensions of HMMs, including in particular hybrids of HMMs with artificial neural networks, InputOutput HMMs (which are conditional HMMs using neural networks to compute probabilities), weighted transducers, variablelength Markov models and Markov switching statespace models. Finally, we discuss some of the challenges of future research in this very active area. 1 Introduction Hidden Markov Models (HMMs) are statistical models of sequential data that have been used successfully in many applications in artificial intelligence, pattern recognition, speech recognition, and modeling of biological ...
A Proof Procedure Using Connection Graphs
 JACM
, 1975
"... ABSTRACT. Various deficiencies of resolution systems are investigated and a new theoremproving system designed to remedy those deficiencms is presented The system is notable for eliminating redundancies present in SLresolutlon, for incorporating preprocessing procedures, for liberahzing the order ..."
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Cited by 77 (5 self)
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ABSTRACT. Various deficiencies of resolution systems are investigated and a new theoremproving system designed to remedy those deficiencms is presented The system is notable for eliminating redundancies present in SLresolutlon, for incorporating preprocessing procedures, for liberahzing the order in which subgoals can be activated, for incorporating multidirectmnal searches, and for giving immediate access to pairs of clauses which resolve Examples of how the new system copes with the defic2encies of other theoremproving systems are chosen from the areas of predicate logic programming and language parsing. The paper emphasizes the historical development of the new system, beginning as a supplement to SLresolution in the form of classificatmn trees and incorporating an analogue of the Waltz algorithm for picture Interpretation The paper ends with a discussion of the opportunities for using lookahead to guide the search for proofs
OPUS: An efficient admissible algorithm for unordered search
 Journal of Artificial Intelligence Research
, 1995
"... OPUS is a branch and bound search algorithm that enables efficient admissible search through spaces for which the order of search operator application is not significant. The algorithmâ€™s search efficiency is demonstrated with respect to very large machine learning search spaces. The use of admissibl ..."
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Cited by 76 (14 self)
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OPUS is a branch and bound search algorithm that enables efficient admissible search through spaces for which the order of search operator application is not significant. The algorithmâ€™s search efficiency is demonstrated with respect to very large machine learning search spaces. The use of admissible search is of potential value to the machine learning community as it means that the exact learning biases to be employed for complex learning tasks can be precisely specified and manipulated. OPUS also has potential for application in other areas of artificial intelligence, notably, truth maintenance. 1.