Reduction of the uncertainty in feature tracking
作者:Anna Gorbenko, Vladimir Popov
摘要
It is difficult to establish feature correspondences between distant viewpoints for panoramic images. For reliable navigation and development a human-like capability of interaction with the surrounding environment, we need a method of reduction of the uncertainty in feature tracking. To obtain a method of reduction of the uncertainty in feature tracking, we propose to use an algorithm for the problem of the longest common subsequence for a set of circular strings. We consider an explicit reduction from the problem of the longest common subsequence for a set of circular strings to the satisfiability problem. This reduction allows to obtain an efficient algorithm for finding the longest common subsequence for a set of circular strings. We present a general scheme of the method of reduction of the uncertainty in feature tracking. We considered the visual homing task to demonstrate the capabilities of our approach to solve the problem of reduction of the uncertainty in feature tracking. We present experimental results for the method of reduction of the uncertainty in feature tracking and novel robot visual homing methods.
论文关键词:Visual navigation, Feature tracking, Mobile robots, Longest common subsequence, Satisfiability problem
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论文官网地址:https://doi.org/10.1007/s10489-018-1236-9