Spatial sensor data processing and analysis for mobile media applications
Guanfeng Wang, Roger Zimmermann · 2014
Currently, an increasing number of user-generated videos (UGVs) are collected and uploaded to the Web -- a trend that is driven by the ubiquitous availability of smartphones and the advances in their camera technology. Additionally, with these sensor-equipped mobile devices, various spatial sensor data (e.g., data from GPS, digital compass etc.) can be continuously acquired in conjunction with the captured video stream without any difficulty. Thus, it has become easy to record and fuse various contextual metadata with UGVs, such as the location and orientation of a camera. This has led to the emergence of large repositories of media contents that are automatically geo-tagged at the fine granularity of frames. Moreover, the collected spatial sensor information becomes a useful and powerful contextual feature to facilitate multimedia/GIS analysis and management in diverse mobile applications. Most sensor information collected from mobile devices, however, is not highly accurate due to two main reasons: (a) the varying surrounding environmental conditions during data acquisition, and (b) the use of low-cost, consumer-grade sensors in current mobile devices. To obtain the best performance from systems that utilize sensor data as important contextual information, highly accurate sensor data input is desirable and efficient sensor data correction algorithms and systems would be extremely useful. Therefore, in this research we aim to enhance the accuracy of such noisy spatial sensor data generated by smartphones during video recording, and utilize this emerging contextual information in mobile applications.