978 resultados para Art objects, Japanese.
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We present the results of an implemented system for learning structural prototypes from grey-scale images. We show how to divide an object into subparts and how to encode the properties of these subparts and the relations between them. We discuss the importance of hierarchy and grouping in representing objects and show how a notion of visual similarities can be embedded in the description language. Finally we exhibit a learning algorithm that forms class models from the descriptions produced and uses these models to recognize new members of the class.
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Under investigation by emission electron microscopy, the shape and size of three-dimensional objects are distorted because of the appearance of a characteristic potential relief and a possible contact potential difference between the particles and the substrate. An estimation of these effects for spherical particles is made. It is shown that the apparent size of particles observed in an emission electron microscope (EEM) could be increased as well as decreased depending on the relation between the work functions of the particle and the substrate. The corresponding formulae are given and several possibilities are shown which permit us to determine from the EEM image the real size of particles and their work function relative to the substrate.
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An approach towards shape description, based on prototype modification and generalized cylinders, has been developed and applied to the object domains pottery and polyhedra: (1) A program describes and identifies pottery from vase outlines entered as lists of points. The descriptions have been modeled after descriptions by archeologists, with the result that identifications made by the program are remarkably consisten with those of the archeologists. It has been possible to quantify their shape descriptors, which are everyday terms in our language applied to many sorts of objects besides pottery, so that the resulting descriptions seem very natural. (2) New parsing strategies for polyhedra overcome some limitations of previous work. A special feature is that the processes of parsing and identification are carried out simultaneously.
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Methods are presented (1) to partition or decompose a visual scene into the bodies forming it; (2) to position these bodies in three-dimensional space, by combining two scenes that make a stereoscopic pair; (3) to find the regions or zones of a visual scene that belong to its background; (4) to carry out the isolation of objects in (1) when the input has inaccuracies. Running computer programs implement the methods, and many examples illustrate their behavior. The input is a two-dimensional line-drawing of the scene, assumed to contain three-dimensional bodies possessing flat faces (polyhedra); some of them may be partially occluded. Suggestions are made for extending the work to curved objects. Some comparisons are made with human visual perception. The main conclusion is that it is possible to separate a picture or scene into the constituent objects exclusively on the basis of monocular geometric properties (on the basis of pure form); in fact, successful methods are shown.
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Is an interactive new media art installation that explores how the sharing of images, normally hidden on mobile phones, can reveal more about people's sense of place and this ultimately shared experience. Traditional views on sense of place, as exemplified by Wagner (1972) and Relph (1976), characterise the experience as a fusion of meaning, act and context. Indeed, Relph suggests that it is not just the identity of a place that is important, but also the identity that a person or group has with that place, in particular whether they are experiencing it as an ‘insider’ or ‘outsider’. This work stimulates debate concerning the impact of technology on sense of place. Technology offers a number of bridges between the real and virtual worlds, but in so doing places an increased tension on the sense of place and subsequently the identity of the individual. This, coupled with the increased use of camera phones, has enabled the documentation of all aspects of our lives, the things we do, the objects we encounter and the places we inhabit. The installation taps into these hidden electronic resources by letting people share their sense of place associated with a large scale event. The work explores the changing nature of the sense of place of performers, visitors and residents over the duration of the event. Interaction with the installation will transform the viewer into performer, echoing Relph’s insider-outsider dichotomy
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Lee M.H. and Nicholls H.R., Tactile Sensing for Mechatronics: A State of the Art Survey, Mechatronics, 9, Jan 1999, pp1-31.
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To be presented at SIG/ISMB07 ontology workshop: http://bio-ontologies.org.uk/index.php To be published in BMC Bioinformatics. Sponsorship: JISC
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X. Zhang and M.H. Lee, 'From Perception to Cognition of Objects', Proceedings of Towards Autonomous Robotic Systems, (TAROS-06), pp 262-67, University of Guildford, Surrey, 2006.
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T.Boongoen and Q. Shen. Semi-Supervised OWA Aggregation for Link-Based Similarity Evaluation and Alias Detection. Proceedings of the 18th International Conference on Fuzzy Systems (FUZZ-IEEE'09), pp. 288-293, 2009. Sponsorship: EPSRC
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Sexton, J. (2008). From Art to Avant Garde? Television, Formalism and the Arts Documentary in 1960's Britain. In L. Mulvey and J. Sexton (Eds.), Experimental British Television (pp.89-105). Manchester: Manchester University Press. RAE2008
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Wydział Historyczny: Instytut Historii Sztuki
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Wydział Historyczny: Instytut Historii Sztuki
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Wydział Historyczny: Instytut Etnologii i Antropologii Kulturowej
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http://www.archive.org/details/japanesewomenspe032256mbp
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The algorithm presented in this paper aims to segment the foreground objects in video (e.g., people) given time-varying, textured backgrounds. Examples of time-varying backgrounds include waves on water, clouds moving, trees waving in the wind, automobile traffic, moving crowds, escalators, etc. We have developed a novel foreground-background segmentation algorithm that explicitly accounts for the non-stationary nature and clutter-like appearance of many dynamic textures. The dynamic texture is modeled by an Autoregressive Moving Average Model (ARMA). A robust Kalman filter algorithm iteratively estimates the intrinsic appearance of the dynamic texture, as well as the regions of the foreground objects. Preliminary experiments with this method have demonstrated promising results.