Corner Detection and Classification of Simple Objects in Low-Depth Resolution Range Images
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Tartalom: https://pp.bme.hu/eecs/article/view/2075
Archívum: PP Electrical Engineering and Computer Science
Gyűjtemény: Articles
Cím:
Corner Detection and Classification of Simple Objects in Low-Depth Resolution Range Images
Létrehozó:
Kovács, Viktor; Budapest University of Technology - Automation and Applied Informatics
Tevesz, Gábor; Budapest University of Technology - Automation and Applied Informatics
Közreműködő:
The work in the paper has been developed in the framework of the project ``Talent care and cultivation in the scientific workshops of BME''. This project is supported by the grant T'AMOP - 4.2.2.B-10/1--2010-0009
Kiadó:
Budapest University of Technology and Economics (BME)
Dátum:
2013-12-09
Téma:
Range image, Corner detection, Feature extraction, Thinning
Tartalmi leírás:
This paper deals with corner detection of simple geometric objects in quantized range images. Low depth resolution and noise introduce challenges in edge and corner detection. Corner detection and classification is based on layer by layer depth data extraction and morphologic operations. Appearance based heuristics are applied to identify different corner types defined in this paper. Both computer generated and captured range images are dealt with. Synthetic range images have arbitrary range resolution while captured images are based on the sensor used. Real world data is collected using a structured light based sensor to provide dense range map.
Nyelv:
angol
Típus:
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Formátum:
application/pdf
Azonosító:
10.3311/PPee.2075
Forrás:
Periodica Polytechnica Electrical Engineering and Computer Science; Vol. 57, No. 1 (2013); 9-17
Kapcsolat:
Létrehozó:
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