The HiBall Tracker: high-performance wide-area tracking for virtual and augmented environments
Proceedings of the ACM symposium on Virtual reality software and technology
Marker Tracking and HMD Calibration for a Video-Based Augmented Reality Conferencing System
IWAR '99 Proceedings of the 2nd IEEE and ACM International Workshop on Augmented Reality
Self-Localization of a Mobile Robot Using Compressed Image Data of Average and Standard Deviation
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
3-D interaction with a large wall display using transparent markers
Proceedings of the International Conference on Advanced Visual Interfaces
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In this paper, we present a new method to perform ego-motion analysis using intensity averaging of image data. The method can estimate general motions from two sequential images on pixel plane by calculating cross correlations. With distance information between camera and objects, this method also enables estimates of camera motion. This method is sufficiently robust even for out of focus image and the calculational overhead is quite low because it uses a simple averaging method. In the future, this method could be used to measure fast motions such as human head tracking, or robot movement. We present a detailed description of the proposed method, and experimental results demonstrating its basic capability. With these results, we verify that our proposed system can detect camera motion even with blurred images. Furthermore, we confirm that it can operate at up to 714 FPS in calculating one dimensional translation motion.