3D OBJECT RECOGNITION USING OCTREE MODEL AND FAST SEARCH ALGORITHM
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F10%3A86075421" target="_blank" >RIV/61989100:27240/10:86075421 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
3D OBJECT RECOGNITION USING OCTREE MODEL AND FAST SEARCH ALGORITHM
Original language description
This paper presents a new approach to 3D object recognition by using an Octree model library (OML) I, II and fast search algorithm. The fast search algorithm is used for finding the 4 pairs of feature points to estimate the viewing direction uses on effective two level database. The method is based on matching the object contour to the reference occluded shapes of 49, 118 viewing directions. The initially bestmatched viewing direction is calibrated by searching for the 4 pairs of feature points betweenthe input image and the image projected along the estimated viewing direction. At this point, the input shape is recognized by matching it to the projected shape. The computational complexity of the proposed method is shown to be O(n(2)) in the worst case, and that of the simple combinatorial method of O(m(4), n(2)) where n and m denote the number of feature points of the 3D model object and the 2D object, respectively.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
NEURAL NETWORK WORLD
ISSN
1210-0552
e-ISSN
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Volume of the periodical
20
Issue of the periodical within the volume
3
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
11
Pages from-to
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UT code for WoS article
000280426100007
EID of the result in the Scopus database
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