Recognition of Faces and Facial Attributes Using Accumulative Local Sparse Representations

dc.contributor.authorMery Quiroz, Domingo Arturo
dc.contributor.authorBanerjee, Sandipan
dc.date.accessioned2022-05-18T14:38:43Z
dc.date.available2022-05-18T14:38:43Z
dc.date.issued2018
dc.description.abstractThis paper addresses the problem of automated recognition of faces and facial attributes by proposing a new general approach called Accumulative Local Sparse Representation (ALSR). In the learning stage, we build a general dictionary of patches that are extracted from face images in a dense manner on a grid. In the testing stage, patches of the query image are sparsely represented using a local dictionary. This dictionary contains similar atoms of the general dictionary that are spatially in the same neighborhood. If the sparsity concentration index of the query patch is high enough, we build a descriptor by using a sum-pooling operator that evaluates the contribution provided by the atoms of each class. The classification is performed by maximizing the sum of the descriptors of all selected patches. ALSR can learn a model for each recognition task dealing with more variability in ambient lighting, pose, expression, occlusion, face size, etc. Experiments on three popular face databases (LFW for faces, AR for gender and Oulu-CASIA for expressions), show that ALSR outperforms representative methods in the literature, when a huge number of training images is not available.
dc.fuente.origenIEEE
dc.identifier.doi10.1109/ICASSP.2018.8462228
dc.identifier.isbn978-1538646588
dc.identifier.issn2379-190X
dc.identifier.urihttps://doi.org/10.1109/ICASSP.2018.8462228
dc.identifier.urihttps://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8462228
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/64150
dc.information.autorucEscuela de ingeniería ; Mery Quiroz, Domingo Arturo ; S/I ; 102382
dc.language.isoen
dc.nota.accesoContenido parcial
dc.publisherIEEE
dc.relation.ispartofIEEE International Conference on Acoustics, Speech and Signal Processing (2018 : Calgary, AB, Canadá)
dc.rightsacceso restringido
dc.subjectDictionaries
dc.subjectFace recognition
dc.subjectTesting
dc.subjectTraining
dc.subjectTask analysis
dc.subjectLighting
dc.subjectComputer vision
dc.titleRecognition of Faces and Facial Attributes Using Accumulative Local Sparse Representationses_ES
dc.typecomunicación de congreso
sipa.codpersvinculados102382
Files