Object localization in weakly labeled images and videos

dc.contributor.authorRochan, Mrigank
dc.contributor.examiningcommitteeBruce, Neil (Computer Science) Leung, Carson (Computer Science) Xu, Wayne (Biochemistry and Medical Genetics)en_US
dc.contributor.supervisorWang, Yang (Computer Science)en_US
dc.date.accessioned2016-09-19T16:55:50Z
dc.date.available2016-09-19T16:55:50Z
dc.date.issued2014-05en_US
dc.date.issued2014-12en_US
dc.date.issued2015-06en_US
dc.degree.disciplineComputer Scienceen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractWe consider the problem of localizing objects in weakly labeled images/videos. An image/video (e.g., Flickr image and YouTube video) is weakly labeled if it is associated with a tag describing the main object present in the image/video. It is weakly labeled because the tag only indicates the presence/absence of the object, but does not provide the detailed spatial location of the object. Given an image/video with an object tag, our goal is to localize the object in it. In this thesis, we propose two novel techniques to handle this challenging problem. First, we build a video-specific object appearance model and then incorporate temporal consistency information to localize the object. Second, we make use of existing detectors of some other object classes (which we call "familiar objects") to build the appearance model of the unseen object class (i.e., the object of interest). Experimental results show the effectiveness of the proposed methods.en_US
dc.description.noteOctober 2016en_US
dc.identifier.citationRochan, Mrigank, et al. "Segmenting objects in weakly labeled videos." Conference on Computer and Robot Vision (CRV), 2014. IEEE, 2014.en_US
dc.identifier.citationRochan, Mrigank, and Yang Wang. "Efficient object localization and segmentation in weakly labeled videos." International Symposium on Visual Computing. Springer International Publishing, 2014.en_US
dc.identifier.citationRochan, Mrigank, and Yang Wang. "Weakly supervised localization of novel objects using appearance transfer." 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2015.en_US
dc.identifier.urihttp://hdl.handle.net/1993/31811
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.publisherSpringer International Publishingen_US
dc.publisherIEEEen_US
dc.rightsopen accessen_US
dc.subjectComputer Visionen_US
dc.subjectObject Localizationen_US
dc.titleObject localization in weakly labeled images and videosen_US
dc.typemaster thesisen_US
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