Abstract
The driving dispute is a critical problem for drivers when the car accident is happened. The drivers usually install the car video recorder in their car to recode their driving images for many years ago. If a car accident is happened, the driver can provide a driving video file as an evidence to claim that they did not do any dangerous driving, and protect themself. However, in some situations, drivers may not in the car accident when driving the car, but they have the same requirement for a video record, because they want to use those video files to find out the crime in hit-and-run accident. Due to an evolution of social network, many people were post the required messages to find the driving videos recorded in some specific times and locations. In fact, such kind of messages can be beneficial for many people to solve the hit-and-run accident by using social networks and driving videos. The goal of this paper is to develop a framework which can provide a platform for users to upload their driving videos, and allow other users can search video by a given specific time, date and location from the frameworks’ database. This framework can also provide the application on mobile devices for user to recorder their driving videos, and this application can upload their driving video into the frameworks’ database automatically.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Masaki, I. (ed.): Vision-based Vehicle Guidance. Springer, New York (1992)
Zheng, Y., Wang, L., Zhang, R., Xie, X., Ma, W.-Y.: GeoLife: Managing and Understanding Your Past Life over Maps. In: Proceeding of the Ninth International Conference on Mobile Data Management, pp. 211–212 (2008)
Lin, D.-H., Jeng, J.-T., Chuang, C.-C., Tao, C.-W.: Intelligent Video Car Recorder systems. In: Proceeding of International Conference on System Science and Engineering (ICSSE), pp. 7–12 (2012)
Chu, S.-T., Yeh, C.-C., Huang, C.-L.: A Cloud-Based Trajectory Index Scheme. In: Proceeding of International Conference on e-Business Engineering, pp. 602–607 (2009)
Almomani, I.M., Alkhalil, N.Y., Ahmad, E.M., Jodeh, R.M.: Ubiquitous GPS vehicle tracking and management system. In: Proceeding of Applied Electrical Engineering and Computing Technologies, pp. 1–6 (2011)
Yang, D., Cai, B., Yuan, Y.: An improved map-matching algorithm used in vehicle navigation system. In: Proceeding of Intelligent Transportation Systems, vol. 2, pp. 1246–1250 (2003)
Marchal, F., Hackney, J., Axhausen, K.W.: Efficient map-matching of large GPS data sets Tests on a speed monitoring experiment in Zurich. Journal of the Transportation Research Board 1935, 93–100 (2005)
Newson, P., Krumm, J.: Hidden Markov map matching through noise and sparseness. In: Proceeding of International Conference on Advances in Geographic Information Systems, pp. 336–343 (2009)
Lou, Y., Zhang, C., Zheng, Y., Xie, X., Wang, W., Huang, Y.: Map-Matching for Low-Sampling-Rate GPS Trajectories. In: Proceeding of International Conference on Advances in Geographic Information Systems, pp. 352–361 (2009)
PostGIS, http://postgis.net/
Institute of Transportation, http://www.iot.gov.tw/mp.asp?mp=1
OpenLayer, http://openlayers.org/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Chiang, CY., Yuan, SM., Yang, SB., Luo, GH., Chen, YL. (2014). Vehicle Driving Video Sharing and Search Framework Based on GPS Data. In: Pan, JS., Krömer, P., Snášel, V. (eds) Genetic and Evolutionary Computing. Advances in Intelligent Systems and Computing, vol 238. Springer, Cham. https://doi.org/10.1007/978-3-319-01796-9_42
Download citation
DOI: https://doi.org/10.1007/978-3-319-01796-9_42
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01795-2
Online ISBN: 978-3-319-01796-9
eBook Packages: EngineeringEngineering (R0)