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Published bySharlene Chambers Modified over 9 years ago
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Viewpoint Selection Based on Fechner Type Information Quantities for 3D Objects † S.Oba † T.Ikai † S.Aoki T.Yamashita†† † M.Izumi K.Fukunaga†† † † Osaka Prefecture University Panasonic Mobile & System Engineering Co., Ltd.
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Related Work Previous study Shannon Entropy Mathematical approach Algorithms for selecting good view Viewpoint Entropy Assumption of good view Largeness of number of visible faces Uniformity of each visible face : all visible face from a viewpoint : face : visible area of face where
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Basic idea of our approach Characteristics Psychophysical approach Selecting a representative view Fechner law Candidate of good view for user Polyhedral object Triangular Mesh of curved object Representative view Unrepresentative view Assumptions Representative view in which amount of visible areas is large amount of changes of curvature is large
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Fechner type information quantity : physical quantity : design parameter Psychophysical law Fechner law logarithmic The relationship between stimulus and sensory response is logarithmic brightness e.g. human : sensory response : stimulus amount lower limit of stimulus amount Fechner law :
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Face Type Shape Information Quantity Information of one face Shape information quantity provides information of one of faces implies face information of 3D object in the brain Face type shape information quantity physical quantity area area = light stimulus amount
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Viewpoint information quantity viewpoint information quantity Information of total visible faces Face Type Viewpoint Information Quantity Face Type Viewpoint Information Quantity receives step function Viewpoint hemisphere where Face type viewpoint information quantity viewpoint
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Edge Type Shape Information Quantity Edge type shape information quantity Relationship between viewpoint and edge line visible face invisible face II I visible face : length of edge : extended curvature viewpoint
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Edge Type Viewpoint Information Quantity Edge I type viewpoint information quantity visible face I : all visible edge from a viewpoint normal vector extended vector
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Edge Type Viewpoint Information Quantity visible face invisible face II Edge II type viewpoint information quantity normal vector : all visible edge from a viewpoint
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Experimental Result ( Polyhedral object ) min max Entropy We show results of Face, Edge I, Edge II, and Entropy Representative view Unrepresentative view Edge I Edge II Face
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Experimental Result ( Curved Object ) Face Edge I Edge II Entropy We show results of Face, Edge I, Edge II, and Entropy min max Representative view Unrepresentative view
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A novel approach for viewpoint selection Conclusions Future work More discussions on the difference among algorithms Fechner type information quantity Shape information quantities Viewpoint information quantities Selecting representative views which have local maximum values of each viewpoint information quantity. Fechner law Face type Edge type Face type Edge type I II
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Chair Horse 1850 meshes Edge I Edge II Entropy Edge I Edge II Face 0.9331 0.93330.5133 0.7753 0.9969 0.7766 Experimental Results ( correlation ) Edge I Edge II Entropy Edge I Edge II Face 0.7284 0.76360.4718 0.6478 0.8473 0.6691 The correlation between proposed algorithms and Entropy method is low value The correlation between Edge I and Edge II is high value Proposed algorithms have high correlation for curved objects Correlation among 3600 viewpoints
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Question and Answer Q. Is there something difference among proposed algorithms ? A. Now, we can’t find difference among proposed algorithms Q. In the case of Moving object, what result can you get ? A. Though it is an expectation, proposed algorithms select same viewpoint as representative view. Q. In the case of non rigid object, what result can you get ? A. If changes of shape is small, the result will hardly change however, if changes of shape is large, it is not likely to be able to select representative views
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Question and Answer Q. In the case of object other than animals, what result can you get ? A. We performed experiment for a airplane model and a house model, we can’ t find difference among proposed algorithms Q. In the case of Free-form Surface, what result can you get ? A. In our algorithms, we presume polyhedron model, so we can ‘t select “good” views for user
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Question and Answer Q. How will you use proposed algorithms ? A. We presume that check system of manufactured article
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