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Filtering by: Creator Stockett, Alan Lee Remove constraint Creator: Stockett, Alan Lee Degree Field Computer Science Remove constraint Degree Field: Computer Science Non-Academic Affiliation Oregon State University. Graduate School Remove constraint Non-Academic Affiliation: Oregon State University. Graduate School

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  • Computational geometry package with fast Voronoi diagram algorithm

    Creator:
    Nave, Jay
    Abstract:
    An interactive Computational geometry package was developed for the purpose of experimenting with geometry problems in the Euclidean plane. The package also contains computer graphics functions to display the result. Application independent functions were developed that are both flexible and general enough for creating new geometry experiments as well as...
    Resource Type:
    Masters Thesis
    Full Text:
    Abstract approved: Redacted for Privacy Alan Coppola An interactive Computational geometry package was

  • Geometric Computer Graphics Package with applications to Steiner's Problem

    Creator:
    Kim, Youn-su
    Abstract:
    An interactive computer graphics package was developed for the purpose of solving certain geometric problems in the Euclidean plane. The Geometric Graphics Package provides basic application-independent functions for creating arbitrary views of two-dimensional objects and for supporting interaction between the application program and its user. The application program contains a...
    Resource Type:
    Masters Thesis

  • An analysis of training methodologies for deep visual trackers

    Creator:
    Fiez, Trevor
    Abstract:
    This thesis considers the problem of training convolutional neural networks for online visual tracking. A major challenge for single object visual tracking is that most training sets with frame-level track annotations are quite small, due to the prohibitive cost of manual annotation. Current training approaches either supplement the annotations with...
    Resource Type:
    Masters Thesis
    Full Text:
    Methodologies for Deep Visual Tracking Abstract approved: Alan Fern Sinisa Todorovic This thesis considers

  • Incorporating and Learning Behavior Constraints for Sequential Decision Making

    Creator:
    Pinto, Jervis
    Abstract:
    Writing a program that performs well in a complex environment is a challenging task. In such problems, a method of deterministic programming combined with reinforcement learning (RL) can be helpful. However, current systems either force developers to encode knowledge in very specific forms (e.g., state-action features), or assume advanced RL...
    Resource Type:
    Dissertation
    Full Text:
    Constraints for Sequential Decision Making Abstract approved: Alan P. Fern Writing a program that performs

  • 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:
    Raw Basketball Videos. Abstract approved: Alan P. Fern Sports analytics is rapidly evolving today

  • Bayesian methods for knowledge transfer and policy search in reinforcement learning

    Creator:
    Wilson, Aaron
    Abstract:
    How can an agent generalize its knowledge to new circumstances? To learn effectively an agent acting in a sequential decision problem must make intelligent action selection choices based on its available knowledge. This dissertation focuses on Bayesian methods of representing learned knowledge and develops novel algorithms that exploit the represented...
    Resource Type:
    Dissertation
    Full Text:
    Tadepalli Alan Fern How can an agent generalize its knowledge to new circumstances? To learn effectively

  • Integrating learning and search for structured prediction

    Creator:
    Doppa, Janardhan Rao
    Abstract:
    We are witnessing the rise of the data-driven science paradigm, in which massive amounts of data - much of it collected as a side-effect of ordinary human activity - can be analyzed to make sense of the data and to make useful predictions. To fully realize the promise of this...
    Resource Type:
    Dissertation
    Full Text:
    : Integrating Learning and Search for Structured Prediction Abstract approved: Prasad Tadepalli Alan P. Fern

  • New learning modes for sequential decision making

    Creator:
    Judah, Kshitij
    Abstract:
    This thesis considers the problem in which a teacher is interested in teaching action policies to computer agents for sequential decision making. The vast majority of policy learning algorithms o er teachers little flexibility in how policies are taught. In particular, one of two learning modes is typically considered: 1)...
    Resource Type:
    Dissertation
    Full Text:
    Modes for Sequential Decision Making Abstract approved: Alan P. Fern This thesis considers the

  • Monte Carlo Tree Search with Fixed and Adaptive Abstractions

    Creator:
    Hostetler, Jesse A.
    Abstract:
    Monte Carlo tree search (MCTS) is a class of online planning algorithms for Markov decision processes (MDPs) and related models that has found success in challenging applications. In the online planning approach, the agent makes a decision in the current state by performing a limited forward search over possible futures...
    Resource Type:
    Dissertation
    Full Text:
    Carlo Tree Search with Fixed and Adaptive Abstractions Abstract approved: Thomas G. Dietterich Alan P

  • Behavior graphs for data-driven animation of 3d characters

    Creator:
    Srinivasan, Madhusudhanan
    Abstract:
    In this dissertation, we present a user-in-the-loop method for the design of an interactive motion data structure that benefits from the advantages of both motion graphs and blend-based techniques. Our novel approach automatically analyzes a traditional motion graph built from labeled motion clips. The result is a more condensed, coarser...
    Resource Type:
    Dissertation
    Full Text:
    posture and spatial constraints. Lee et al. [31] also combine motion graphs with clustering. Frames