477,159 research outputs found

    Characterization of modulated time-of-flight range image sensors

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    A number of full field image sensors have been developed that are capable of simultaneously measuring intensity and distance (range) for every pixel in a given scene using an indirect time-of-flight measurement technique. A light source is intensity modulated at a frequency between 10–100 MHz, and an image sensor is modulated at the same frequency, synchronously sampling light reflected from objects in the scene (homodyne detection). The time of flight is manifested as a phase shift in the illumination modulation envelope, which can be determined from the sampled data simultaneously for each pixel in the scene. This paper presents a method of characterizing the high frequency modulation response of these image sensors, using a pico-second laser pulser. The characterization results allow the optimal operating parameters, such as the modulation frequency, to be identified in order to maximize the range measurement precision for a given sensor. A number of potential sources of error exist when using these sensors, including deficiencies in the modulation waveform shape, duty cycle, or phase, resulting in contamination of the resultant range data. From the characterization data these parameters can be identified and compensated for by modifying the sensor hardware or through post processing of the acquired range measurements

    Shape and deformation measurement using heterodyne range imaging technology

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    Range imaging is emerging as a promising alternative technology for applications that require non-contact visual inspection of object deformation and shape. Previously, we presented a solid-state full-field heterodyne range imaging device capable of capturing three-dimensional images with sub-millimetre range resolution. Using a heterodyne indirect time-of-flight configuration, this system simultaneously measures distance (and intensity), for each pixel in a cameras field of view. In this paper we briefly describe our range imaging system, and its principle of operation. By performing measurements on several metal objects, we demonstrate the potential capabilities of this technology for surface profiling and deformation measurement. In addition to verifying system performance, the reported examples highlight some important system limitations. With these in mind we subsequently discuss the further developments required to enable the use of this device as a robust and practical tool in non-destructive testing and measurement applications

    An experiment with ontology mapping using concept similarity

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    This paper describes a system for automatically mapping between concepts in different ontologies. The motivation for the research stems from the Diogene project, in which the project's own ontology covering the ICT domain is mapped to external ontologies, in order that their associated content can automatically be included in the Diogene system. An approach involving measuring the similarity of concepts is introduced, in which standard Information Retrieval indexing techniques are applied to concept descriptions. A matrix representing the similarity of concepts in two ontologies is generated, and a mapping is performed based on two parameters: the domain coverage of the ontologies, and their levels of granularity. Finally, some initial experimentation is presented which suggests that our approach meets the project's unique set of requirements

    Optimal measurement of visual motion across spatial and temporal scales

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    Sensory systems use limited resources to mediate the perception of a great variety of objects and events. Here a normative framework is presented for exploring how the problem of efficient allocation of resources can be solved in visual perception. Starting with a basic property of every measurement, captured by Gabor's uncertainty relation about the location and frequency content of signals, prescriptions are developed for optimal allocation of sensors for reliable perception of visual motion. This study reveals that a large-scale characteristic of human vision (the spatiotemporal contrast sensitivity function) is similar to the optimal prescription, and it suggests that some previously puzzling phenomena of visual sensitivity, adaptation, and perceptual organization have simple principled explanations.Comment: 28 pages, 10 figures, 2 appendices; in press in Favorskaya MN and Jain LC (Eds), Computer Vision in Advanced Control Systems using Conventional and Intelligent Paradigms, Intelligent Systems Reference Library, Springer-Verlag, Berli

    Similarity of Semantic Relations

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    There are at least two kinds of similarity. Relational similarity is correspondence between relations, in contrast with attributional similarity, which is correspondence between attributes. When two words have a high degree of attributional similarity, we call them synonyms. When two pairs of words have a high degree of relational similarity, we say that their relations are analogous. For example, the word pair mason:stone is analogous to the pair carpenter:wood. This paper introduces Latent Relational Analysis (LRA), a method for measuring relational similarity. LRA has potential applications in many areas, including information extraction, word sense disambiguation, and information retrieval. Recently the Vector Space Model (VSM) of information retrieval has been adapted to measuring relational similarity, achieving a score of 47% on a collection of 374 college-level multiple-choice word analogy questions. In the VSM approach, the relation between a pair of words is characterized by a vector of frequencies of predefined patterns in a large corpus. LRA extends the VSM approach in three ways: (1) the patterns are derived automatically from the corpus, (2) the Singular Value Decomposition (SVD) is used to smooth the frequency data, and (3) automatically generated synonyms are used to explore variations of the word pairs. LRA achieves 56% on the 374 analogy questions, statistically equivalent to the average human score of 57%. On the related problem of classifying semantic relations, LRA achieves similar gains over the VSM

    Lightweight Sensing Uncertainty Metric – Incorporating Accuracy and Trust

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    Video-rate or high-precision: A flexible range imaging camera

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    A range imaging camera produces an output similar to a digital photograph, but every pixel in the image contains distance information as well as intensity. This is useful for measuring the shape, size and location of objects in a scene, hence is well suited to certain machine vision applications. Previously we demonstrated a heterodyne range imaging system operating in a relatively high resolution (512-by-512) pixels and high precision (0.4 mm best case) configuration, but with a slow measurement rate (one every 10 s). Although this high precision range imaging is useful for some applications, the low acquisition speed is limiting in many situations. The system’s frame rate and length of acquisition is fully configurable in software, which means the measurement rate can be increased by compromising precision and image resolution. In this paper we demonstrate the flexibility of our range imaging system by showing examples of high precision ranging at slow acquisition speeds and video-rate ranging with reduced ranging precision and image resolution. We also show that the heterodyne approach and the use of more than four samples per beat cycle provides better linearity than the traditional homodyne quadrature detection approach. Finally, we comment on practical issues of frame rate and beat signal frequency selection

    Multiple-sensor integration for efficient reverse engineering of geometry

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    This paper describes a multi-sensor measuring system for reverse engineering applications. A sphere-plate artefact is developed for data unification of the hybrid system. With the coordinate data acquired using the optical system, intelligent feature recognition and segmentation algorithms can be applied to extract the global surface information of the object. The coordinate measuring machine (CMM) is used to re-measure the geometric features with a small amount of sampling points and the obtained information can be subsequently used to compensate the point data patches which are measured by optical system. Then the optimized point data can be exploited for accurate reverse engineering of CAD model. The limitations of each measurement system are compensated by the other. Experimental results validate the accuracy and effectiveness of this data optimization approach

    Task Specific Uncertainty in Coordinate Measurement

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    Task specific uncertainty is the measurement uncertainty associated with the measurement of a specific feature using a specific measurement plan. This paper surveys techniques developed to model and estimate task specific uncertainty for coordinate measuring systems, primarily coordinate measuring machines using contacting probes. Sources of uncertainty are also reviewed
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