This thesis aims at investigating on 3D Computer Vision, a research topic which is gathering even increasing attention thanks to the more and more widespread availability of affordable 3D visual sensor, such as, in particular consumer grade RGB-D cameras.
The contribution of this dissertation is twofold. First, the work addresses how to compactly represent the content of images acquired with RGB-D cameras. Second, the thesis focuses on 3D Reconstruction, key issue to efficiently populate the databases of 3D models deployed in object/category recognition scenarios.
As 3D Registration plays a fundamental role in 3D Reconstruction, the former part of the thesis proposes a pipeline for coarse registration of point clouds that is entirely based on the computation of 3D Local Reference Frames (LRF). Unlike related work in literature, we also propose a comprehensive experimental evaluation based on diverse kinds of data (such as those acquired by laser scanners, RGB-D and stereo cameras) as well as on quantitative comparison with respect to three other methods.
Driven by the ever-lower costs and growing distribution of 3D sensing devices, we expect broad-scale integration of depth sensing into mobile devices to be forthcoming.
Accordingly, the thesis investigates on merging appearance and shape information for Mobile Visual Search and focuses on encoding RGB-D images in compact binary codes.
An extensive experimental analysis on three state-of-the-art datasets, addressing both category and instance recognition scenarios, has led to the development of an RGB-D search engine architecture that can attain high recognition rates with peculiarly moderate bandwidth requirements.
Our experiments also include a comparison with the CDVS (Compact Descriptors for Visual Search) pipeline, candidate to become part of the MPEG-7 standard.
| Identifer | oai:union.ndltd.org:unibo.it/oai:amsdottorato.cib.unibo.it:7410 |
| Date | 13 May 2016 |
| Creators | Petrelli, Alioscia <1979> |
| Contributors | Di Stefano, Luigi |
| Publisher | Alma Mater Studiorum - Università di Bologna |
| Source Sets | Università di Bologna |
| Language | English |
| Detected Language | English |
| Type | Doctoral Thesis, PeerReviewed |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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