![]() Redžić MD Laoudias C Kyriakides I Image and WLAN bimodal integration for Indoor user localization IEEE Trans. In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. ![]() Indoor localization via multi-modal sensing on smartphones. In: 2018 21st International Conference on Information Fusion (FUSION), pp. Multi-camera matching of spatio-temporal binary features. Vinav: a vision-based indoor navigation system for smartphones IEEE Trans. In: Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval, pp. Lu, G., Song, J.: 3D Image-based Indoor localization joint with WiFi positioning. In: Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems, pp. imoon: Using smartphones for image based indoor navigation. Fusion of magnetic and visual sensors for indoor localization: infrastructure-free and more effective IEEE Trans. In: 2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), pp. Xu, J., Yang, Z., Chen, H., et al.: Embracing spatial awareness for reliable WiFi-based Indoor location systems. Wu C Yang Z Liu Y Wireless Indoor Localization: A Crowdsourcing Approach 2018 Springer 10.1007/978-981-13-0356-2 Google Scholar Digital Library Wu C Yang Z Xiao C Automatic radio map adaptation for indoor localization using smartphones IEEE Trans. In: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. Xu, H., Yang, Z., Zhou, Z., et al.: Enhancing wifi-based localization with visual clues. Peer-to-peer indoor navigation using smartphones IEEE J. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. ![]() Understanding the limitations of cnn based absolute camera pose regression. ![]() Sattler, T., Zhou, Q., Pollefeys, M., et al. Shah, R., Aditya D., and Narayanan, P.J.: Multistage SfM: A coarse-to-fine approach for 3d reconstruction. Experimental analysis on weight K-nearest neighbor indoor fingerprint positioning IEEE Internet Things J. ![]() A survey on wireless indoor localization from the device perspective ACM Comput. The experimental results show that EfiLoc can achieve good positioning accuracy and is of better robustness to the environment of weak textures and similar scenes compared with current state-of-the-art vision-based solutions. Preserving the associations of the pixels in some key areas of the image, the precise and quick large-scale indoor localization can be realized. Second, we innovatively implement the efficient association of 3D point with the 2D features generated by its projection regions. Another property is that the generated sparser main global descriptors can greatly reduce the retrieval time of multi-dimensional features. First, we develop a lightweight network model, which can quickly extract discriminative global deep features to improve the discrimination of similar scenes. We design and realize the positioning system for large indoor scenes called the EfiLoc. However, the 3D model-based indoor positioning is still an open issue to be addressed, especially in large-scale dynamic environments. Important location information of a query image can be obtained directly through indoor 3D points. ![]()
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