A User Behavior Driven Display Technique for Augmented Reality System

• Main Authors: Jia-Chung Kao, 高嘉駿
• Other Authors: Jiung-Yao Huang
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/78404520264711828749

碩士 === 國立臺北大學 === 資訊工程學系 === 102 === With the evolvement of mobile augmented reality(MAR) technology, its hardware platform range from handheld device to head mounted display in the past. Along with the advancement of embedded technology into lighter and thinner in the recent years, the applications of augmented reality on various wearable devices are massively proposed. The Google glass is one good example of such development. However, the wearable MAR applications always face the issues of limited screen display size that increase the cognitive load to the user and unhandy interface that obstruct the interaction with augmented information. To solve above cognitive load and Human-Computer Interaction(HCI) problems, this research proposes an adaptive augmented information display method that are based on the user's behavior. The approach started from building the user behavior model when they are using the mobile augmented reality system. The behavior features that are accessable from wearable device are then identified. These behavior features become an important clue to identify the behavior states of the user. That is, the feature data are used to classify the possible current state of the user. However, due to the unpredictable environment interference to the sensors, the feature data along can’t accuratly determine the user’s behavior. Therefore, the study further applied the past behavior of the user, when he was using MAR stsem, to predict his current possible behavior state. The predicted state and clssified state are then cross-referenced to infer the most likely user’s motion state. In order to verify the proposed method, the study takes the commonly available augmented reality application, Augmented Reality Browser, as an example to develop a prototype system. Based on user’s behavior when using a MAR system, the prototype system categorize user motion into five states: stationary state, stationary but look around state, turning while moving state, moving and staring state, and searching while moving state. The display pattern of each state is then designed. The system is then adaptive switch among these display patterns according to perceived five states. The research goal is to improve the efficiency of searching surrounding augmented information when the user is using AR Browser so that the application of MAR can seamlessly integrate into our daily life. In the future, the user's personal profile can be further integrated into perception process to provide more adaptive augmented service based upon user's current state.