基于消防安全疏散标志的高精度室内视觉定位

为解决室内交通无法利用GPS进行定位的问题,针对室内普遍存在并且均匀分布的消防安全疏散标志,研究了基于消防安全疏散标志的高精度室内视觉定位算法.以计算当前位置距离地图中最近的1个消防安全疏散标志地点的位姿为目标,利用消防安全疏散标志的颜色特性进行颜色阈值分割.结合方向梯度直方图(HOG)特征与支持向量机(SVM)检测候选框中是否含有消防安全疏散标志,然后用加速鲁棒特征(SURF)全局特征进行特征匹配,利用最邻近(KNN)方法选取全局特征距离最小的K个地点作为候选定位结果.用SURF局部特征进行特征匹配,选取局部特征匹配数目最多的1个地点作为图像级定位结果,并计算当前位置在地图中的位姿.通过在地下停车场和大型办公楼进行实地测试,图像级定位的准确率在96% 以上,平均定位误差在0.6 m以下.实验结果表明,该算法满足了室内定位精度的需求,并具有良好的鲁棒性. 

High-accuracy Vision-based Indoor Positioning Using Building Safety Evacuation Signs

As GPS signals are blocked in indoor environments,a vision-based accurate indoor positioning algorithm is proposed referring to fire safety evacuation signs which are widely and evenly distributed in indoor environments.The algorithm aims at calculating distance to the nearest fire safety evacuation sign in the map from the pose of current posi-tion.Color character of fire safety evacuation signs is used for color threshold segmentation.Histogram of Oriented Gra-dient(HOG)features and Support Vector Machine(SVM)are combined to check whether the candidate box contains a fire safety evacuation sign.Holistic Speeded Up Robust Features(SURF)is used for matching,and K-Nearest Neighbor (KNN)method is uses to select nearest K positions as candidate locations.SURF local feature is used for feature matc-hing,a location with the largest number of local feature matches is selected as the result of image-level positioning,and the pose of the current location is calculated in the map.Through the field test in an underground parking lot and an office building,the results show that the proposed method can meet the requirements of accurate indoor positioning,with the accuracy is above 96%,and the average positioning error is below 0.6 m.The results show that this proposed method provides a robust and accurate solution for indoor positioning.