Title

Implementing a gesture-based matchmaking system in an audio exercise game

Date of Publication

2017

Document Type

Master's Thesis

Degree Name

Master of Science in Computer Science

College

College of Computer Studies

Department/Unit

Computer Science

Thesis Adviser

Raymund C. Sison

Defense Panel Chair

Rafael A. Cabredo

Defense Panel Member

Raymund C. Sison
Solomon L. See
Merlin Teodosia C. Suarez

Abstract/Summary

Many games utilize matchmaking to improve the gaming experience for the players of the game. In this research, the use of skill-based versus style-based matchmaking is explored under the context of a Boxing Audio Exercise Game. Player actions, which are retrieved through the Kinect Sensor, are used to determine how each player plays the Boxing Audio Exercise Game.

An 82.5% detection rate was achieved for the gesture recognition using the Hidden Markov Model. These gestures were then used to extract four clusters that describe the playing styles possible for the Shadow Boxing Game. The four clusters include players that focus primarily on attack (Aggressive Type), players that focus on determining the appropriate response to the opponents attack (Counter Punchers), players who beat all the objectives of the game (Completionists), and players who perform the least when compared with the other participants (Strugglers).

Abstract Format

html

Language

English

Format

Electronic

Accession Number

CDTG007127

Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

Physical Description

1 computer disc ; 4 3/4 in.

Keywords

Computer games; Internet games; Video games; Electronic games

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