Browse Dissertations and Theses - Electrical and Computer Engineering by Contributor "Hoiem, Derek W."

  • Hedau, Varsha (2012-02-06)
    An image is nothing but a projection of the physical world around us, where objects do not occur randomly but follow certain spatial rules. Many existing computer vision approaches tend to ignore this aspect of understanding ...

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  • Wang, Gang (2011-01-14)
    Visual recognition is a fundamental research topic in computer vision. This dissertation explores datasets, features, learning, and models used for visual recognition. In order to train visual models and evaluate ...

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  • Zhou, Zihan (2013-05-24)
    Driven by emergent needs in industrial applications such as film production, navigation and virtual reality, the problem of inferring 3D structures of urban scenes from 2D images has recently drawn a lot of interest in the ...

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  • Akbas, Emre (2011-08-26)
    This dissertation is about extracting as well as making use of the structure and hierarchy present in images. We develop a new low-level, multiscale, hierarchical image segmentation algorithm designed to detect image ...

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  • Khorrami, Pooya Rezvani (2017-03-29)
    As technological systems become more and more advanced, the need for including the human during the interaction process has become more apparent. One simple way is to have the computer system understand and respond to the ...

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  • Bhobe, Sujay (2013-05-24)
    This thesis presents an approach to predict the occupied area on the floor in an image of an indoor scene. The goal is to be able to obtain navigable areas even in cluttered indoor environments. This algorithm could be ...

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  • Yang, Qingxiong (2011-01-21)
    In this dissertation, I report the progress towards building a robust and efficient 3D reconstruction system based on stereo vision. Stereo vision is known to be quite fragile in practice due to specular highlights, lack ...

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  • Dikmen, Mert (2012-06-27)
    Detection and recognition of objects in images is one of the most impor- tant problems in computer vision. In this thesis we adhere to a traditional bottom–up detection and recognition framework, where the objects are ...

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