Indoor navigation landmark extraction method

Abstract

The invention provides an indoor navigation landmark extraction method. The method comprises the following steps: firstly, acquiring landmark saliency attribute data from an indoor scene picture to obtain a landmark saliency attribute measurement value; standardizing the landmark saliency attribute measurement value to obtain final landmark saliency attribute data; meanwhile, obtaining a landmarksaliency value in a questionnaire survey mode; dividing the final landmark saliency attribute data and landmark saliency values into a training set, a verification set and a test set by adopting a five-fold cross validation method, and obtaining a final landmark saliency model by utilizing a genetic programming algorithm according to the training set, the verification set and the test set; and finally, using the final landmark saliency model for calculating the saliency value of each landmark, and extracting the landmark with the highest saliency value. The method has the advantages that the quantitative relation between the landmark significance attribute data and the landmark significance is accurately represented, the prediction accuracy of the most saliency landmark is improved, and the method has practicability.

Description

technical field [0001] The invention relates to the field of indoor location and navigation services, in particular to a method for extracting indoor navigation landmarks. Background technique [0002] Landmarks are salient entities on people's cognition maps of real and virtual indoor and outdoor environments, and they are crucial in pedestrians' cognition of unfamiliar environments, especially in wayfinding. Compared with traditional navigation instructions based on distance and bearing, especially in complex indoor and outdoor environments, landmark-based wayfinding methods are generally considered to be effective in increasing pedestrian confidence, reducing their anxiety during navigation, and helping pedestrians navigate smoothly. reach the destination. Therefore, a variety of landmark-based wayfinding methods have emerged in recent years. [0003] The challenge of landmark-based navigation methods is how to choose the correct landmarks. For example, there may be mu...

AI Technical Summary

Problems solved by technology

However, these linear models may affect the accuracy of quantitatively representing the relationship between landmark attributes and their saliency

Existing landmark extraction models are all linear, and the commonly used linear models to measure landmark saliency cannot accurately represent the quantitative relationship between landmark attributes and saliency

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