Fast and smart object proposals for object detection

dc.contributor.authorAmrane, Abdesalam
dc.contributor.authorMeziane, Abdelkrim
dc.contributor.authorBoulekrinat, Houda
dc.contributor.authorAtik, Ali
dc.description.abstractObject localization plays an important role in object detection and classification. In the last years, several methods have shifted from sliding windows techniques to object proposals techniques. The latter produces a small set of windows submitted to an object classifier to reduce the computational time. In this paper, we propose a fast unsupervised method that combines the edge feature and saliency map to generate less than hundred bounding boxes from the processed image. Our approach exploits a number of rules based on edges information plus saliency regions to decide if an object is present in a window. We have carried out several experiments to validate our approach on ImageNet dataset and obtained very promising results.fr_FR
dc.relation.ispartofRapports de recherche internes
dc.structureSystèmes et Documents Multimédia Structurés (SDMS)fr_FR
dc.subjectObject proposalsfr_FR
dc.subjectBounding boxfr_FR
dc.subjectObject detectionfr_FR
dc.subjectSaliency mapfr_FR
dc.subjectSliding windowfr_FR
dc.titleFast and smart object proposals for object detectionfr_FR
dc.typeTechnical Report