Project Details
COVMAP-2: Continuation of Comprehensive Conjoint GPS, Sensor and Video Data Analysis for Next Generation of Smart Maps
Subject Area
Geodesy, Photogrammetry, Remote Sensing, Geoinformatics, Cartography
Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
Security and Dependability, Operating-, Communication- and Distributed Systems
Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
Security and Dependability, Operating-, Communication- and Distributed Systems
Term
from 2016 to 2021
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 314236227
During the last years the availability of spatial data has rapidly developed. Characteristic for this development is the involvement of large number of users, who frequently use smart phones and mobile devices, to generate and make freely available Volunteered Geographic Information (VGI). Whereas GPS and gyroscope data (e.g. with fitness-straps) are common, the huge amount of data, which are easily and typically collected in the form of videos, make video analysis based methods very demanding. On the other hand, only videos allow for a comprehensive scene interpretation. In this research project, we are interested in combining GPS, gyroscope and video data to analyze road and traffic situations for cyclists and pedestrians. Our standard setting is a smart phone attached to a bicycle, which records the GPS coordinates, videos, (online) local weather information and time. We will (a) use the GPS-data for integration in a map, (b) local velocities and gyroscope data, as well as variations in the sensor data, will be used to identify important situations during a bicycle ride, and (c) video data will be used to understand these important situation which causes e.g. a delay in the ride.The analyzed data can then be used for map enhancement and path recommendation, but also for the identification of unclear road marks which is important for city planning and accident avoidance. Besides collecting experience with real-time and event triggered data with a focus on a human-centered application, the foundations can easily be extended towards traffic management after hazards, quality control of topographic datasets or environmental and health-related data analysis using additional sensor information.
DFG Programme
Priority Programmes
Subproject of
SPP 1894:
Volunteered Geographic Information: Interpretation, Visualisation and Social Computing
International Connection
Netherlands
Cooperation Partner
Professor Dr.-Ing. Michael Ying Yang