On-line adaptive visual tracking

Salti, Samuele (2011) On-line adaptive visual tracking , [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Ingegneria elettronica, informatica e delle telecomunicazioni, 23 Ciclo. DOI 10.6092/unibo/amsdottorato/3735.
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Visual tracking is the problem of estimating some variables related to a target given a video sequence depicting the target. Visual tracking is key to the automation of many tasks, such as visual surveillance, robot or vehicle autonomous navigation, automatic video indexing in multimedia databases. Despite many years of research, long term tracking in real world scenarios for generic targets is still unaccomplished. The main contribution of this thesis is the definition of effective algorithms that can foster a general solution to visual tracking by letting the tracker adapt to mutating working conditions. In particular, we propose to adapt two crucial components of visual trackers: the transition model and the appearance model. The less general but widespread case of tracking from a static camera is also considered and a novel change detection algorithm robust to sudden illumination changes is proposed. Based on this, a principled adaptive framework to model the interaction between Bayesian change detection and recursive Bayesian trackers is introduced. Finally, the problem of automatic tracker initialization is considered. In particular, a novel solution for categorization of 3D data is presented. The novel category recognition algorithm is based on a novel 3D descriptors that is shown to achieve state of the art performances in several applications of surface matching.

Tipologia del documento
Tesi di dottorato
Salti, Samuele
Dottorato di ricerca
Scuola di dottorato
Scienze e ingegneria dell'informazione
Settore disciplinare
Settore concorsuale
Parole chiave
adaptive tracking Kalman filter surface matching background subtraction
Data di discussione
28 Aprile 2011

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