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Stochastic visual tracking with active appearance models
Thesis (PhD (Applied Mathematics))--University of Stellenbosch, 2009.
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| Format: | Thesis |
| Language: | English |
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Stellenbosch : University of Stellenbosch
2009
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| _version_ | 1867613909535424512 |
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| access_status_str | Open Access |
| author | Hoffmann, McElory Roberto |
| author2 | Herbst, B. M. |
| author_browse | Herbst, B. M. Hoffmann, McElory Roberto |
| author_facet | Herbst, B. M. Hoffmann, McElory Roberto |
| author_sort | Hoffmann, McElory Roberto |
| collection | Thesis |
| dc_rights_str_mv | University of Stellenbosch |
| description | Thesis (PhD (Applied Mathematics))--University of Stellenbosch, 2009. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/1381 |
| institution | Stellenbosch University (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:43:38.086Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2009 |
| publishDateRange | 2009 |
| publishDateSort | 2009 |
| publisher | Stellenbosch : University of Stellenbosch |
| publisherStr | Stellenbosch : University of Stellenbosch |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/1381 Stochastic visual tracking with active appearance models Hoffmann, McElory Roberto Herbst, B. M. Hunter, K. Van Zijl, L. Du Preez, J. University of Stellenbosch. Faculty of Engineering. Dept. of Mathematical Sciences. Applied Mathematics. Active appearance models Particle filters Tracking Dissertations -- Applied mathematics Theses -- Applied mathematics Stochastic models Computer vision Thesis (PhD (Applied Mathematics))--University of Stellenbosch, 2009. ENGLISH ABSTRACT: In many applications, an accurate, robust and fast tracker is needed, for example in surveillance, gesture recognition, tracking lips for lip-reading and creating an augmented reality by embedding a tracked object in a virtual environment. In this dissertation we investigate the viability of a tracker that combines the accuracy of active appearancemodels with the robustness of the particle lter (a stochastic process)—we call this combination the PFAAM. In order to obtain a fast system, we suggest local optimisation as well as using active appearance models tted with non-linear approaches. Active appearance models use both contour (shape) and greyscale information to build a deformable template of an object. ey are typically accurate, but not necessarily robust, when tracking contours. A particle lter is a generalisation of the Kalman lter. In a tutorial style, we show how the particle lter is derived as a numerical approximation for the general state estimation problem. e algorithms are tested for accuracy, robustness and speed on a PC, in an embedded environment and by tracking in ìD. e algorithms run real-time on a PC and near real-time in our embedded environment. In both cases, good accuracy and robustness is achieved, even if the tracked object moves fast against a cluttered background, and for uncomplicated occlusions. AFRIKAANSE OPSOMMING: ’nAkkurate, robuuste en vinnige visuele-opspoorderword in vele toepassings benodig. Voorbeelde van toepassings is bewaking, gebaarherkenning, die volg van lippe vir liplees en die skep van ’n vergrote realiteit deur ’n voorwerp wat gevolg word, in ’n virtuele omgewing in te bed. In hierdie proefskrif ondersoek ons die lewensvatbaarheid van ’n visuele-opspoorder deur die akkuraatheid van aktiewe voorkomsmodellemet die robuustheid van die partikel lter (’n stochastiese proses) te kombineer—ons noem hierdie kombinasie die PFAAM. Ten einde ’n vinnige visuele-opspoorder te verkry, stel ons lokale optimering, sowel as die gebruik van aktiewe voorkomsmodelle wat met nie-lineêre tegnieke gepas is, voor. Aktiewe voorkomsmodelle gebruik kontoer (vorm) inligting tesamemet grysskaalinligting om ’n vervormbaremeester van ’n voorwerp te bou. Wanneer aktiewe voorkomsmodelle kontoere volg, is dit normaalweg akkuraat,maar nie noodwendig robuust nie. ’n Partikel lter is ’n veralgemening van die Kalman lter. Ons wys in tutoriaalstyl hoe die partikel lter as ’n numeriese benadering tot die toestand-beramingsprobleem afgelei kan word. Die algoritmes word vir akkuraatheid, robuustheid en spoed op ’n persoonlike rekenaar, ’n ingebedde omgewing en deur volging in ìD, getoets. Die algoritmes loop intyds op ’n persoonlike rekenaar en is naby intyds op ons ingebedde omgewing. In beide gevalle, word goeie akkuraatheid en robuustheid verkry, selfs as die voorwerp wat gevolg word, vinnig, teen ’n besige agtergrond beweeg of eenvoudige okklusies ondergaan. Doctoral 2009-11-17T13:55:56Z 2010-06-01T08:20:08Z 2009-11-17T13:55:56Z 2010-06-01T08:20:08Z 2009-12 Thesis http://hdl.handle.net/10019.1/1381 en University of Stellenbosch application/pdf Stellenbosch : University of Stellenbosch |
| spellingShingle | Active appearance models Particle filters Tracking Dissertations -- Applied mathematics Theses -- Applied mathematics Stochastic models Computer vision Hoffmann, McElory Roberto Stochastic visual tracking with active appearance models |
| title | Stochastic visual tracking with active appearance models |
| title_full | Stochastic visual tracking with active appearance models |
| title_fullStr | Stochastic visual tracking with active appearance models |
| title_full_unstemmed | Stochastic visual tracking with active appearance models |
| title_short | Stochastic visual tracking with active appearance models |
| title_sort | stochastic visual tracking with active appearance models |
| topic | Active appearance models Particle filters Tracking Dissertations -- Applied mathematics Theses -- Applied mathematics Stochastic models Computer vision |
| url | http://hdl.handle.net/10019.1/1381 |
| work_keys_str_mv | AT hoffmannmceloryroberto stochasticvisualtrackingwithactiveappearancemodels |