Improving the Motion Processing Hierarchy for Attending to Visual Motion

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dc.contributor.advisorTsotsos, John K.
dc.contributor.authorZhang, Xiao Lei
dc.date.accessioned2024-03-18T17:59:07Z
dc.date.available2024-03-18T17:59:07Z
dc.date.issued2024-03-16
dc.date.updated2024-03-16T10:50:59Z
dc.degree.disciplineElectrical and Computer Engineering
dc.degree.levelMaster's
dc.degree.nameMASc - Master of Applied Science
dc.description.abstractVisual motion has been studied for decades now. Attention to motion using Selective Tuning involves a top-down selection mechanism within a feed-forward motion hierarchy. Researchers have proposed various models for the motion hierarchy. In this thesis, we introduce a learnable hierarchy, based on fully convolutional networks, ST-Motion-Net. The Selective Tuning model for visual attention is demonstrated on ST-Motion-Net to localize motion patterns and segment moving objects. We create two datasets, Blender-MP and Blender-Complex, to evaluate ST-Motion-Net on motion pattern detection, localization, and motion segmentation tasks. ST-Motion-Net achieves excellent performance on motion pattern detection and localization for each area of ST-Motion-Net. For motion segmentation, we evaluate 2-Frame-Area-V1 of ST-Motion-Net on the task. 2-Frame-V1 contains neurons that respond to translation motion, given 2 most recent frames of a temporal sequence. 2-Frame-V1 achieves 86.84% IoU on Blender-MP-Test, which surpass some state-of-the-art models. On Blender-Complex-Test, 2-Frame-V1 reaches 52.61% IoU, which also achieves state-of-the-art performance.
dc.identifier.urihttps://hdl.handle.net/10315/41877
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectComputer engineering
dc.subjectComputer science
dc.subjectNeurosciences
dc.subject.keywordsVisual motion analysis
dc.subject.keywordsSelective tuning
dc.subject.keywordsAffine motion
dc.subject.keywordsConvolutional neural networks
dc.subject.keywordsMotion segmentation
dc.titleImproving the Motion Processing Hierarchy for Attending to Visual Motion
dc.typeElectronic Thesis or Dissertation

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