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3D geometry-based face recognition in presence of eye and mouth occlusions
Abstract This study proposes a novel occlusions detection and restoration strategy. The aim is to success with 3D face recognition even when faces are partially occluded by external objects. The method, which relies on geometrical facial properties, is designed for managing two types of facial occlusions (eye and mouth occlusions due to hands). First occlusions are detected and (if present) classified, by considering their effects on the 3D points cloud. Then, the occluded regions are progressively removed, and finally, the non-occluded symmetrical regions are used to restore the missing information. After the restoration process, face recognition is performed relying on the restored facial information and on the localized landmarks. The landmarking methodology relies on derivatives and on 12 differential geometry descriptors. The discriminating features adopted for facial comparison include shape index histograms, Euclidean and geodetical distances between landmarks, facial curves, and nose volume. Obtained recognition rates, evaluated on the whole Bosphorus database and on our private dataset, ranging from 92.55 to 97.20% depending on the completeness of data.
3D geometry-based face recognition in presence of eye and mouth occlusions
Abstract This study proposes a novel occlusions detection and restoration strategy. The aim is to success with 3D face recognition even when faces are partially occluded by external objects. The method, which relies on geometrical facial properties, is designed for managing two types of facial occlusions (eye and mouth occlusions due to hands). First occlusions are detected and (if present) classified, by considering their effects on the 3D points cloud. Then, the occluded regions are progressively removed, and finally, the non-occluded symmetrical regions are used to restore the missing information. After the restoration process, face recognition is performed relying on the restored facial information and on the localized landmarks. The landmarking methodology relies on derivatives and on 12 differential geometry descriptors. The discriminating features adopted for facial comparison include shape index histograms, Euclidean and geodetical distances between landmarks, facial curves, and nose volume. Obtained recognition rates, evaluated on the whole Bosphorus database and on our private dataset, ranging from 92.55 to 97.20% depending on the completeness of data.
3D geometry-based face recognition in presence of eye and mouth occlusions
Dagnes, Nicole (author) / Marcolin, Federica (author) / Nonis, Francesca (author) / Tornincasa, Stefano (author) / Vezzetti, Enrico (author)
2019-05-25
19 pages
Article (Journal)
Electronic Resource
English
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