Publications
This is a list of published articles that I have worked on.Understanding Information Observation in an Interactive 3D Environment
Authors: Priyesh N. Dixit, G. Michael YoungbloodConference: Sandbox Symposium 2008
Abstract: Communicating information to the user is a vital part of the interactive experience. In order to better convey the information to the end user, we must know where to place this information and how to present it in a manner that it will be noticed. Subjectively placing this information is not sufficient since every user will interact with the environment in their own unique manner. Information value is a metric that provides us with the knowledge of which surfaces players looked at most in the environment in the form of an ordered list of surfaces. Using an objective algorithm for discovering the information value of environmental surfaces from recorded player data, we performed a 150 subject information value study and found that placing information in the high value surfaces yields up to 60% improvement in user observation. However, most players did not recall the information that they had seen. We conducted another 150 subject study to investigate what factors improve information retention and found that popular images do improve recall by up to 28%. Finally, we conducted a 30 person study on the effect of changing the player's task (context) from search to exploration on information recall and found that recall increased by 38%.
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ACM Digital Library (Coming Soon)
Automatically-generated Convex Region Decomposition for Real-time Spatial Agent Navigation and Information Compartmentalization
Authors: D. Hunter Hale, G. Michael Youngblood, and Priyesh N. DixitConference: AAAI 2008 (Accepted as poster)
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Utilizing Interactive 3D Game Player Data for Knowledge Discovery and Visualization
Authors: Priyesh N. DixitPublication: UNCC Masters Thesis (2008)
Abstract: It is often difficult to construct a 3D environment, but it is even more challenging when the environment must be interactive. This is because every user (player) will interact with the environment in their own unique manner. Gaining feedback through play testing is a common method for evaluating such information in these environments. However, the process of improving the experience from user collected data can be unclear. Visual representation of this game player information can help provide insight into the data in order to discover patterns and behavior that would otherwise be hidden. We explored the use of visual data mining and automated data processing to process the logged player data and present the results of finding 5 unique phenomena in our dataset of 3079 players. These phenomena include pirouettes, flusters, jumpers, learning, and emergent behavior. We also investigated an algorithm for discovering the information value of environmental surfaces from player data. This information value metric provides us with the knowledge of where players look in the environment in the form of an ordered list of surfaces. We performed a 150 subject information value study and found that placing information in the high value surfaces yields up to 60% improvement in user observation. However, most players did not recall the information. We then conducted another 150 subject study to investigate what factors improve information retention and found that popular images do improve recall by up to 28%. Finally, we conducted a 30 person study on the effect of changing the player's task (context) from search to exploration on information recall and found that recall did increase by 38%.
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Understanding Intelligence in Games using Player Traces and Interactive Player Graphs
Authors: G. Michael Youngblood, Priyesh N. DixitPublication: Game Programming Gems 7 (2008)
Chapter 3.5, pgs. 265-280
Optimal Information Placement in an Interactive 3D Environment
Authors: Priyesh N. Dixit, G. Michael YoungbloodConference: Sandbox Symposium 2007
Abstract: The correct placement of important artifacts and information in interactive three-dimensional (3D) environments is important to ensure that those key artifacts and information are seen and absorbed by the immersed user. This can include training information, advertisements, clues, interaction points, and other information that needs to be conveyed to or manipulated by the user. We propose a novel algorithm for calculating the optimal positioning of such artifacts and information based on a corpus of prior play testers, which are used to determine distance-weighted and radially focused observation densities on surfaces of interactive 3D environments. We have developed a tool called HIIVVE (Highly Interactive Information Value Visualization and Evaluation) which allows for interactive evaluation as well as offline processing of the information value surfaces. A user study involving information placement using the calculated information value surfaces and observation densities shows that higher valued locations do yield improved user observation by as much as 58.3%.
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ACM Digital Library