Abstract
When a user wants to know how far he is away from an object in sight, a typical method is to search the target object in a map application which relies on GPS for distance estimation. This method fails if the target is not listed in the map or GPS signals are not available, such as in a tunnel or in the wild. This paper presents CamDist, a ranging system using the camera of a smartphone. CamDist takes two photos of the target in the direction from the user to the target, and performs distance estimation based on the size difference of the target in the two photos and the moving distance of the smartphone between taking two photos. CamDist has a novel accelerometer based moving distance estimation module that adaptively rotates the smartphone’s axis and gives accurate distance estimation. The estimation method applies to other scenarios when the smartphone moves in a direction orthogonal to gravity, and is better than the built-in rotation method of the smartphone. We provide theoretical analysis on the estimation error of CamDist, and show that the working range of CamDist depends on the resolution of the camera as well as the physical size of the remote target. Also, a series of real-world experiments are conducted to verify the effectiveness of CamDist.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Guo, S., Chen, S., Liu, F., Ye, X., Yang, H.: Binocular vision-based underwater ranging methods. In: 2017 IEEE International Conference on Mechatronics and Automation (ICMA), pp. 1058–1063 (2017)
Han, H., Yi, S., Li, Q., Shen, G., Liu, Y., Novak, E.: AMIL: localizing neighboring mobile devices through a simple gesture. In: Proceedings of IEEE INFOCOM, pp. 1–9 (2016)
Haseeb, M.A., Guan, J., Ristic-Durrant, D., Gräser, A.: DisNet: a novel method for distance estimation from monocular camera. 10th Planning, Perception and Navigation for Intelligent Vehicles (PPNIV18) (2018)
Jia, L., et al.: A high-resolution ultrasonic ranging system using laser sensing and a cross-correlation method. Appl. Sci. 9(7), 1483 (2019)
Kim, I., Yow, K.C.: Object location estimation from a single flying camera. In: The Ninth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (2015)
Krishnan, J.V.G., Manoharan, N., Rani, B.S.: Estimation of distance to texture surface using complex log mapping. J. Comput. Appl. 3(3), 16 (2010)
Kwon, Y., Kwon, K.: RSS ranging based indoor localization in ultra low power wireless network. AEU-Int. J. Electron. Commun. 104, 108–118 (2019)
Mankoff, K.D., Russo, T.A.: The kinect: a low-cost, high-resolution, short-range 3D camera. Earth Surf. Process. Landf. 38(9), 926–936 (2013)
Mazraani, R., Saez, M., Govoni, L., Knobloch, D.: Experimental results of a combined TDOA/TOF technique for UWB based localization systems. In: 2017 IEEE International Conference on Communications Workshops (ICC Workshops), pp. 1043–1048 (2017)
Peyman, A.: Object distance measurement using a single camera for robotic applications. Diss. Laurentian University of Sudbury (2015)
Wang, W., Huang, J., Cai, S., Yang, J.: Design and implementation of synchronization-free TDOA localization system based on UWB. Radioengineering 27(1), 320–330 (2019)
Wang, Y., Zhu, X., Xu, L.: Flight path optimization for UAVs to provide location service to ground targets. In: Proceedings of WCNC (2020)
Wang, Y., Zhu, X., Han, H.: ChirpMu: Chirp based imperceptible information broadcasting with music. In: Proceedings of IWQoS (2021)
Wikipedia: Lens (2021). https://en.wikipedia.org/wiki/Lens
Wu, J., Zhu, J., Yang, L., Shen, M., Xue, B., Liu, Z.: A highly accurate ultrasonic ranging method based on onset extraction and phase shift detection. Measurement 47, 433–441 (2014)
Yenamandra, V., Uttama Nambi, A., Padmanabhan, V., Navda, V., Srinivasan, K.: CamMirror: single-camera-based distance estimation for physical analytics applications. In: Proceedings of the 4th International on Workshop on Physical Analytics, pp. 25–30 (2017)
Yi, S., Suh, J., Hong, Y., Hwang, D.: Active ranging system based on structured laser light image. In: Proceedings of SICE Annual Conference 2010, pp. 747–752 (2010)
Zhang, L., Zhu, X., Wu, X.: No more free riders: sharing WIFI secrets with acoustic signals. In: Proceedings of ICCCN (2019)
Zhu, X., Li, Q., Chen, G.: APT: accurate outdoor pedestrian tracking with smartphones. In: Proceedings of IEEE INFOCOM (2013)
Zhu, X., Wu, X., Chen, G.: Relative localization for wireless sensor networks with linear topology. Comput. Commun. 36(15–16), 1581–1591 (2013)
Acknowledgements
This work was supported by the National Natural Science Foundation of China (61972199), Jiangsu Hydraulic Science and Technology Project (No. 2020061) and Hydraulic Research Institute of Jiangsu Province (No. 2020z025).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Zhu, Y., Zhu, X., Qian, C. (2021). CamDist: Camera Based Distance Estimation with a Smartphone. In: Liu, Z., Wu, F., Das, S.K. (eds) Wireless Algorithms, Systems, and Applications. WASA 2021. Lecture Notes in Computer Science(), vol 12937. Springer, Cham. https://doi.org/10.1007/978-3-030-85928-2_26
Download citation
DOI: https://doi.org/10.1007/978-3-030-85928-2_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-85927-5
Online ISBN: 978-3-030-85928-2
eBook Packages: Computer ScienceComputer Science (R0)