A Bayesian approach for object classification based on clusters of SIFT local features

dc.creatorLeonardo Chang Fernández
dc.creatorLuis Enrique Sucar Succar
dc.creatorEduardo Francisco Morales Manzanares
dc.date2012
dc.date.accessioned2023-07-25T16:24:55Z
dc.date.available2023-07-25T16:24:55Z
dc.identifierhttp://inaoe.repositorioinstitucional.mx/jspui/handle/1009/2079
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7807260
dc.descriptionSeveral methods have been presented in the literature that successfully used SIFT features for object identification, as they are reasonably invariant to translation, rotation, scale, illumination and partial occlusion. However, they have poor performance for classification tasks. In this work, SIFT features are used to solve object class recognition problems in images using a two-step process. In its first step, the proposed method performs clustering on the extracted features in order to characterize the appearance of the different classes. Then, in the classification step, it uses a three layer Bayesian network for object class recognition. Experiments show quantitatively that clusters of SIFT features are suitable to represent classes of objects. The main contributions of this paper are the introduction of a Bayesian network approach in the classification step to improve performance in an object class recognition task, and a detailed experimentation that shows robustness to changes in illumination, scale, rotation and partial occlusion.
dc.formatapplication/pdf
dc.languageeng
dc.publisherElsevier Ltd.
dc.relationcitation:Chang-Fernández, L., et al., (2012). A Bayesian approach for object classification based on clusters of SIFT local features, Expert Systems with Applications, Num. (39): 1679–1686
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.subjectinfo:eu-repo/classification/Object class recognition/Object class recognition
dc.subjectinfo:eu-repo/classification/Local features/Local features
dc.subjectinfo:eu-repo/classification/SIFT/SIFT
dc.subjectinfo:eu-repo/classification/Clustering/Clustering
dc.subjectinfo:eu-repo/classification/Bayesian networks/Bayesian networks
dc.subjectinfo:eu-repo/classification/cti/1
dc.subjectinfo:eu-repo/classification/cti/12
dc.subjectinfo:eu-repo/classification/cti/1203
dc.subjectinfo:eu-repo/classification/cti/1203
dc.titleA Bayesian approach for object classification based on clusters of SIFT local features
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.audiencestudents
dc.audienceresearchers
dc.audiencegeneralPublic


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