DEVELOPMENT OF POINT CLOUD DESCRIPTORS FOR ROBUST 3D RECOGNITION
Object recognition allows machines to understand the nature of objects it encounters in the surrounding environment. Descriptors are the most important element for robust object recognition system as they assign a unique identification to each object that withstands pose and illumination variatio...
| Main Author: | OSMAN ALI, YASIR SALIH |
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| Format: | Thesis |
| Language: | English |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-utpedia.21543 / |
| Published: |
2015
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| Subjects: | |
| Online Access: |
http://utpedia.utp.edu.my/21543/1/2015%20-ELECTRICAL%20%26%20ELECTRONIC%20-%20DEVELOPMENT%20OF%20POINT%20CLOUD%20DESCRIPTORS%20FOR%20ROBUST%203D%20RECOGNITION%20-%20YASIR%20SALIH%20OSMAN%20ALI.pdf http://utpedia.utp.edu.my/21543/ |
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| Summary: |
Object recognition allows machines to understand the nature of objects it
encounters in the surrounding environment. Descriptors are the most important
element for robust object recognition system as they assign a unique identification to
each object that withstands pose and illumination variations. Among many surface
descriptors proposed in the literature, orientation based descriptors are the most
commonly used, however they are represented with large and sparse histograms.
Moreover, existing descriptors are highly susceptible to noise and viewpoint
variations. These limitation prevented object recognition algorithms from being
implemented on embedded devices (e.g: smartphones) and mobile robots specially for
mapping applications. |
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