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Filtering by: Creator Little, David Remove constraint Creator: Little, David Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Subject Computer vision Remove constraint Subject: Computer vision

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  • Object highlighting : real-time boundary detection using a Bayesian network

    Creator:
    Jia, Jin
    Abstract:
    Image segmentation continues to be a fundamental problem in computer vision and image understanding. In this thesis, we present a Bayesian network that we use for object boundary detection in which the MPE (most probable explanation) before any evidence can produce multiple non-overlapping, non-self-intersecting closed contours and the MPE with...
    Resource Type:
    Masters Thesis
    Full Text:
    thank Professor Ron Metoyer, Professor Prasad Tadepalli and Professor David Birkes for being on my

  • Interactive player tracking for videos in American football

    Creator:
    Bawaskar, Amit
    Abstract:
    This thesis presents an interactive software tool for tracking a moving object in a video. In particular, we focus on the problem of tracking a player in American football videos. Object tracking is one of the fundamental problems in computer vision. It is one of the most important components in...
    Resource Type:
    Masters Thesis
    Full Text:
    of the art in tracking usually takes into account little to no camera motion. Existing trackers

  • 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
    Full Text:
    , Sean Mc- Gregor, and Tuan Pham for this. Thanks, too, to Chris Chambers, David Piorkowski, Eric Walk

  • 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
    Full Text:
    thank Sheng Chen, Behrooz Mahasseni, David Stuve and Anirban Roy for their assistance and advises

  • Region based image matching for 3D object recognition

    Creator:
    Liu, Tian
    Abstract:
    3D object recognition is a very difficult and important problem in computer vision, arising in a wide range of applications. Typically in 3D object recognition, interest points are extracted from images and then matched. A shortcoming of this approach is that points only carry local visual information. Therefore, there could...
    Resource Type:
    Masters Thesis
    Full Text:
    little work on 3D object recognition in comparison to research in 2D object recognition [2] [25]. While

  • 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

  • From multitarget tracking to event recognition in videos

    Creator:
    Brendel, William
    Abstract:
    This dissertation addresses two fundamental problems in computer vision—namely, multitarget tracking and event recognition in videos. These problems are challenging because uncertainty may arise from a host of sources, including motion blur, occlusions, and dynamic cluttered backgrounds. We show that these challenges can be successfully addressed by using a multiscale,...
    Resource Type:
    Dissertation

  • Hierarchical graphical models for activity recognition in videos

    Creator:
    Amer, Mohamed R.
    Abstract:
    This dissertation addresses the problem of recognizing human activities in videos. Our focus is on activities with stochastic structure, where the activities are characterized by variable space-time arrangements of actions, and conducted by a variable number of actors. These activities occur frequently in sports and surveillance videos. They may appear...
    Resource Type:
    Dissertation