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30 April 1992 Introduction of explicit sensor models in error recovery
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Abstract
The application of numeric methods to the minimization of error has become an emerging paradigm for obj ect recovery. Typically, a parametric representation describing the object is postulated. Its parameters are then adjusted to minimize some measurement of the distance between the representation and the datapoints (the error-of-fit model). Characteristics of the sensor used to recover the points may be implicit in this formulation or may not be included at all. While sensors may be precise for a specific field of view no sensor is everywhere exact. A laser range finder for example, yields very sharp x- and y-coordinate values; however, its z-coordinate is less trustworthy. It becomes important to capture the strengths and weaknesses of a sensor and incorporate them into the recovery process. We seek to make explicit the contribution of a particular sensor by introducing a sensor model. This partitioning facilitates the development of an appropriate description of a sensor's characteristics. Also, it helps clarify interactions among different aspects of the recovery process ( i.e. error-of-fit model, sensor model, and parametric object representation). The sensor model is reflected in the certainty of sensed quantities (position, color, intensity) associated with a datapoint. We explore whether the introduction of an explicit sensor model yields an improvement in the recovery process. The PROVER (Parametric Representation Of Volumes: Experimental Recovery) System, a testbed used in the development of sensor models is described.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas P. O'Donnell and Terrance E. Boult "Introduction of explicit sensor models in error recovery", Proc. SPIE 1611, Sensor Fusion IV: Control Paradigms and Data Structures, (30 April 1992); https://doi.org/10.1117/12.57914
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