DiVerdi Stephen, Höllerer Tobias
Adobe Systems Inc., Santa Barbara, CA 93106-5110, USA.
IEEE Trans Vis Comput Graph. 2008 May-Jun;14(3):500-12. doi: 10.1109/TVCG.2008.26.
Anywhere Augmentation pursues the goal of lowering the initial investment of time and money necessary to participate in mixed reality work, bridging the gap between researchers in the field and regular computer users. Our paper contributes to this goal by introducing the GroundCam, a cheap tracking modality with no significant setup necessary. By itself, the GroundCam provides high frequency, high resolution relative position information similar to an inertial navigation system, but with significantly less drift. We present the design and implementation of the GroundCam, analyze the impact of several design and run-time factors on tracking accuracy, and consider the implications of extending our GroundCam to different hardware configurations. Motivated by the performance analysis, we developed a hybrid tracker that couples the GroundCam with a wide area tracking modality via a complementary Kalman filter, resulting in a powerful base for indoor and outdoor mobile mixed reality work. To conclude, the performance of the hybrid tracker and its utility within mixed reality applications is discussed.
Anywhere增强技术致力于降低参与混合现实工作所需的初始时间和资金投入,弥合该领域研究人员与普通计算机用户之间的差距。我们的论文通过引入GroundCam(一种无需大量设置的廉价跟踪方式)来助力这一目标。GroundCam本身就能提供类似于惯性导航系统的高频、高分辨率相对位置信息,但漂移明显更小。我们介绍了GroundCam的设计与实现,分析了几个设计和运行时因素对跟踪精度的影响,并考虑了将GroundCam扩展到不同硬件配置的意义。基于性能分析,我们开发了一种混合跟踪器,它通过互补卡尔曼滤波器将GroundCam与广域跟踪方式相结合,为室内外移动混合现实工作打造了一个强大的基础。最后,我们讨论了混合跟踪器的性能及其在混合现实应用中的效用。