OSCOR: An orientation sensor data correction system for mobile generated contents

Abstract

In addition to positioning data, other sensor information - such as orientation data, have become a useful and powerful contextual feature. Such auxiliary information can facilitate higher-level semantic description inferences in many multi- media applications, e.g., video tagging and video summa- rization. However, sensor data collected from current mobile devices is often not accurate enough for upstream multime- dia analysis. An effective orientation data correction system for mobile multimedia content has been an elusive goal so far. Here we present a system, termed Oscor, which aims to improve the accuracy of noisy orientation sensor measure- ments generated by mobile devices during image and video recording. We provide a user-friendly camera interface to facilitate the gathering of additional information, which en- Ables the correction process on the server-side. Geographic field-of-view (FOV) visualizations based on the original and corrected sensor data help users understand the corrected contextual information and how the erroneous data possibly may affect further processes. Copyright © 2013 ACM.