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Extending CLP(FD) with Interactive Data Acquisition for 3D Visual Object Recognition

03/2000;
Source: CiteSeer

ABSTRACT This paper addresses the 3D object recognition problem modelled as a Constraint Satisfaction Problem. In this setting, each object view can be modelled as a constraint graph where nodes are object parts and constraints are topological and geometrical relationships among them. By modelling the problem as a CSP, we can recognize an object when all constraints are satisfied by exploiting results from the CSP field. However, in classical CSPs variable domains have to be statically defined at the beginning of the constraint propagation process. Thus, not only feature acquisition should be completed before the constraint solving process starts, but all image features should be extracted even if not belonging to significant image parts. In visual applications, this requirement turns out to be inefficient since visual features acquisition is a very time consuming task. We present an Interactive Constraint Satisfaction model for problems where variable domains may not be completely known at...

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    • "An example is given by Faltings and Macho-Gonzalez (2003) where Internet applications are faced and obviously not all the information can be computed before starting the constraint satisfaction process. As another example, consider a visual search system (Cucchiara et al. 1999b) where domain elements are basic visual features (like segments, points, or surface patches) extracted from the image. In a classical CLP(FD) computation, all domain values must be known when defining the variables, so all the possible visual features would have to be extracted before starting the visual search process, even if only a small subset of them will be actually used. "
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    ABSTRACT: In classical CLP(FD) systems, domains of variables are completely known at the beginning of the constraint propagation process. However, in systems interacting with an external environment, acquiring the whole domains of variables before the beginning of constraint propagation may cause waste of computation time, or even obsolescence of the acquired data at the time of use. For such cases, the Interactive Constraint Satisfaction Problem (ICSP) model has been proposed as an extension of the CSP model, to make it possible to start constraint propagation even when domains are not fully known, performing acquisition of domain elements only when necessary, and without the need for restarting the propagation after every acquisition. In this paper, we show how a solver for the two sorted CLP language, defined in previous work, to express ICSPs, has been implemented in the Constraint Handling Rules (CHR) language, a declarative language particularly suitable for high level implementation of constraint solvers.
    Theory and Practice of Logic Programming 09/2004; DOI:10.1017/S147106840500236X · 0.90 Impact Factor
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    • "An example is given by Faltings and Macho-Gonzalez (2003) where Internet applications are faced and obviously not all the information can be computed before starting the constraint satisfaction process. As another example, consider a visual search system (Cucchiara et al. 1999b) where domain elements are basic visual features (like segments, points, or surface patches) extracted from the image . In a classical CLP(FD) computation, all domain values must be known when defining the variables, so all the possible visual features would have to be extracted before starting the visual search process, even if only a small subset of them will be actually used. "
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    ABSTRACT: In classical CLP(FD) systems, domains of variables are completely known at the beginning of the constraint propagation process. However, in systems interacting with an external environment, acquiring the whole domains of variables before the beginning of constraint propagation may cause waste of computation time, or even obsolescence of the acquired data at the time of use. For such cases, the Interactive Constraint Satisfaction Problem (ICSP) model has been proposed as an extension of the CSP model, to make it possible to start constraint propa- gation even when domains are not fully known, performing acquisition of domain elements only when necessary and without the need to restart propagation after every acquisition. In this paper, we present a two sorted CLP language to express and solve ICSPs, and its implementation in the Constraint Handling Rules (CHR) language, a declarative language particularly suitable for high level implementation of constraint solvers.
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    ABSTRACT: Research paper (M.S.)--Southern Illinois University at Carbondale, Dept. of Computer Science, 1990. Non-circulating archival copy. Vita. Includes bibliographical references (leaves 52-53).
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