Towards Robust Camera Tracking in Cluttered Visual Environments
ABSTRACT:
It has long been of interest in computer vision and more recently in the robotics community to estimate camera motion from a sequence of images (structure from motion/simultaneous location and mapping). Traditionally, this requires tracking visual features such as corners or lines between at least two frames and possibly over the duration of the video sequence. We present a novel particle-filter based algorithm for estimating camera motion which combines feature tracking and motion estimation within the same framework.
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