Matches in UGent Biblio for { <https://biblio.ugent.be/publication/688193#aggregation> ?p ?o. }
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- aggregation classification "P1".
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation date "2008".
- aggregation format "application/pdf".
- aggregation hasFormat 688193.bibtex.
- aggregation hasFormat 688193.csv.
- aggregation hasFormat 688193.dc.
- aggregation hasFormat 688193.didl.
- aggregation hasFormat 688193.doc.
- aggregation hasFormat 688193.json.
- aggregation hasFormat 688193.mets.
- aggregation hasFormat 688193.mods.
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- aggregation hasFormat 688193.xls.
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- aggregation isPartOf urn:isbn:9783540884576.
- aggregation isPartOf urn:issn:0302-9743.
- aggregation language "eng".
- aggregation publisher "Springer".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Languages and Literatures".
- aggregation title "Object tracking using naive Bayesian classifiers".
- aggregation abstract "This work presents a tracking algorithm based on a set of naive Bayesian classifiers. We consider tracking as a, classification problem and train a set of classifiers which distinguish a target object from the background around it. Classifiers' voting make a soft decision about class adherence for each pixel in video frame, forming a confidence map. We use the mean shift. algorithm to find the nearest peak in the confidence map, with respect to the previous position of the target. The location of that peak represents the new position of the object. The temporal adaptivity of the tracker is achieved by gradual update of a target model. The results demonstrate ability of the proposed method to perforin successful tracking in different environmental conditions.".
- aggregation authorList BK278519.
- aggregation endPage "784".
- aggregation startPage "775".
- aggregation volume "5259".
- aggregation aggregates 4260459.
- aggregation isDescribedBy 688193.
- aggregation similarTo LU-688193.