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Filtering by: Creator Baehr, Matthew M. Remove constraint Creator: Baehr, Matthew M. Subject Computer vision Remove constraint Subject: Computer vision

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  • Implementing High Dynamic Range (HDR) Photography to Improve 3D Laser Scanning Point Cloud Visualization and Segmentation

    Creator:
    Mahmoudabadi, Hamid
    Abstract:
    This research explores several novel approaches to improve visualization and segmentation of point clouds acquired with 3D laser scanning. 3D laser scanning is used in a wide variety of applications including surveying and mapping, transportation asset management, facilities management, building information modeling, crime scene investigations, cultural heritage and geologic instigations....
    Resource Type:
    Dissertation

  • Learning affinities of exemplar videos for multi-view action recognition

    Creator:
    Roy, Anirban
    Abstract:
    This thesis addresses a fundamental computer vision problem, that of action recognition. The goal of action recognition is to recognize a class of human actions in a given video. Action recognition has a wide range of applications, including automated surveillance, sports video analysis, internet-based searches etc. The main challenge is...
    Resource Type:
    Masters Thesis
    Full Text:
    Mi fea- tures, we define an Mj ×Mi similarity matrix, Xji = [Xji(m,n)], where Xji(m,n)≥0 represents

  • Pixel- and Frame-level Video Labeling using Spatial and Temporal Convolutional Networks

    Creator:
    Lei, Peng
    Abstract:
    This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
    Resource Type:
    Dissertation

  • A study of methods for fine-grained object classification of arthropod specimens

    Creator:
    Lin, Junyuan
    Abstract:
    Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained...
    Resource Type:
    Masters Thesis
    Full Text:
    descriptors per image M Dimension of a local descriptor d Number of spatial bins for pyramid representation

  • Toward computer vision for understanding American football in video

    Creator:
    Hess, Robin W.
    Abstract:
    In this work, I examine the problem of understanding American football in video. In particular, I present several mid-level computer vision algorithms that each accomplish a different sub-task within a larger system for annotating, interpreting, and analyzing collections of American football video. The analysis of football video is useful in...
    Resource Type:
    Dissertation

  • Automatic Detection of Possessions and Shots from Raw Basketball Videos

    Creator:
    Terhuja, Vikedo
    Abstract:
    Sports analytics is rapidly evolving today through the use of computer vision systems that automatically extract huge amount of information inherently present in multimedia data without much human assistance. This information can facilitate a better understanding of patterns and strategies in various sports. However, for non-professional teams, due to expense...
    Resource Type:
    Masters Thesis

  • Robust and Efficient Classification of Videos in the Wild

    Creator:
    Mahasseni, Behrooz
    Abstract:
    Recognizing human actions in videos is a long-standing problem in computer vision with a wide range of applications including video surveillance, content retrieval, and sports analysis. This thesis focuses on addressing efficiency and robustness of video classification in unconstrained real-world settings. The thesis work can be broadly divided into four...
    Resource Type:
    Dissertation
    Full Text:
    the action class; and h denotes the space-time locations of the win- dows in A. For a set of M action