移动增强现实中基于视觉—惯性传感器的混合跟踪方法研究

项目名称： 移动增强现实中基于视觉—惯性传感器的混合跟踪方法研究

项目编号： No.61502188

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 计算机科学学科

项目作者： 杨欣

作者单位： 华中科技大学

项目金额： 23万元

中文摘要： 随着智能手机的飞速发展和普及，移动增强现实应用受到学术界和工业界的广泛关注。姿态跟踪作为移动增强现实中的核心技术成为了迫切需要。然而，传统的移动增强现实跟踪技术通常基于单一的视觉方法或者传感器方法，很难同时满足跟踪精度、鲁棒性和实时性的需求。本课题致力于研究新的融合视觉与惯性传感器的混合跟踪模型以实现智能手机上精确、鲁棒、实时的跟踪。围绕混合跟踪模型中三个具体难点开展深入研究，具体包括： 轻量级在线的特征选择算法；多源传感器融合跟踪方法；基于视觉-传感器数据融合跟踪方法及自适应突变误差校验。本课题将有力推动移动增强现实的理论和应用的发展，为提供一种移动环境下全新的人机交互方式提供核心算法与技术。

中文关键词： 移动增强现实；三维注册；自然特征；混合跟踪；智能手机

英文摘要： With fast development and deployment of smartphones, mobile augmented reality (MAR) on smartphones has attracted increasing interests from academia and industry. Pose tracking is one of the most critical tasks in an MAR system. However, conventional methods which rely on only visual features or inertial sensors are either too computationally expensive on smartphones, or not sufficiently accurate and robust for a satisfactory user experience. This proposal focuses on developing a novel hybrid tracking system and address key challenges in the system, including: lightweight online feature selection for robust feature tracking, multimodel sensor data fusion for inertial tracking, adaptive Kalman filtering with abrupt error verification for vision-inertial hybrid tracking. The research conducted in this proposal will provide robust and efficient pose tracking techniques which can run efficiently on mobile phones. Meanwhile, it will significantly speedup the development of MAR theories and facilitate wide deployment of MAR apps.

英文关键词： mobile augmented reality;3D registration;natural features;hybrid tracking;smartphones