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dc.contributor.advisorLu, Yijuan
dc.contributor.authorYe, Yuxiang
dc.date.accessioned2016-06-13T19:03:51Z
dc.date.available2016-06-13T19:03:51Z
dc.date.created2016-05
dc.date.issued2016-04-26
dc.date.submittedMay 2016
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/6050
dc.description.abstractHuman’s sketch understanding is an important and challenging research problem. It has many applications in human computer interaction, multimedia, and computer vision. Most previous methods focus on single-object sketch recognition. Human’s scene sketch understanding has not been studied. In this work, we make the first attempt to tackle this problem. We create the first scene sketch dataset “Scene250” and explore deep learning scheme for scene sketch understanding. We propose a deep CNN model “Scene-Net” and build a novel scene sketch recognition system based on this model. Our system has been tested on the collected scene sketch dataset and compared with other state-of-the-art CNNs and sketch recognition approaches. We also extend our work to sketch-based 3D model retrieval and design a complete retrieval system (CNN-SBR) based on deep CNN. It also achieves better performance than other comparison systems. The experimental results demonstrate the effectiveness and potential of our method.
dc.formatText
dc.format.extent57 pages
dc.format.medium1 file (.pdf)
dc.language.isoen_US
dc.subjectDeep learning
dc.subjectConvolutional neural network
dc.subjectPattern recognition
dc.subject.lcshComputer vision
dc.subject.lcshOptical data processing
dc.subject.lcshComputer graphics
dc.subject.lcshImage processing--Digital techniques
dc.titleApplying deep learning to scene sketch recognition and 3D sketch-based 3D model retrieval
txstate.documenttypeThesis
dc.contributor.committeeMemberGao, Byron
dc.contributor.committeeMemberChen, Xiao
thesis.degree.departmentComputer Scienceen_US
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.grantorTexas State Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
txstate.departmentComputer Science


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