Browsing by Author "Dr. Benjamin Watson, Committee Member"

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    An Accumulative Framework for Object Recognition
    (2009-04-21) Krish, Karthik; Dr. Wesley E. Snyder, Committee Chair; Dr. Hamid Krim, Committee Member; Dr. Griff Bilbro, Committee Member; Dr. Siamak Khorram, Committee Member; Dr. Benjamin Watson, Committee Member
    Object recognition has received a lot of attention over the years and has reached a level where we have a lot of algorithms which can identify a large number of previously seen objects. We have algorithms which deal only with recognizing shapes and algorithms which are suited for recognizing objects in cluttered scenes using shape, color and texture. This dissertation provides a unified framework which can be applied not only to recognize simple shapes such as silhouettes but also recognize real objects in cluttered environments with occlusion. The framework presented in this dissertation uses an accumulative approach reminiscent of the well known Generalized Hough Transform introduced by Ballard to recognize general shapes. Accumulator-based methods are highly parallel and use simple arithmetic. Noise and isotropic distortions tend to average out. The algorithm is invariant to translation, rotation, scale (zoom) and robust to illumination changes, background clutter, occlusion as well as view point changes. This is demonstrated using a wide range of data sets and experiments where it is shown to significantly outperform the current state-of-the-art. The novel contributions of this dissertation are as follows: 1. A unified matching algorithm which matches different object models by accumulating features in a higher dimensional space. 2. A general and unified object representation (or model) built using robust and invariant features, extracted based on the nature of the object.
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    Automatic Identification and Generation of Highlight Cinematics in 3D Games
    (2010-02-16) Dominguez, Michael; Dr. R. Michael Young, Committee Chair; Dr. Benjamin Watson, Committee Member; Dr. Robert St. Amant, Committee Member
    Online multiplayer gaming has emerged as a popular form of entertainment. During these games, the players' main focus is usually placed on achieving the objectives that must be completed to win the game. While these tasks may be of the primary interest to the players, over the course of the game their interactions may result in interesting narratives that go unnoticed. This may be due to the imperfect information that a player has access to or as a result of their attention being directed towards accomplishing the goals of the game. This thesis presents Afterthought, a system that will allow players to view these emergent narratives after completing their gameplay session. The tool accomplishes this through logging the actions that occur during the play of the game, analyzing the log and retrieving interesting narratives, generating the cinematic discourse for visualization, rendering the videos of the narratives, and finally uploading the videos to a video sharing site so that they are easily viewable by all participants. This thesis concludes with preliminary human subjects evaluation of the system's effectiveness.