Location-aware video capturing and sharing for mobile users

Funding Details
Natural Sciences and Engineering Research Council of Canada
  • Grant type: Engage Grants Program
  • Year: 2012/13
  • Total Funding: $25,000
Keywords
Principle Investigator(s)
Collaborator(s)

No researchers found.

Partners

Project Summary

Incorporated May 2009, the company Pica is developing patent pending cross platform mobile and location based software applications, which are expected to enable efficient media capturing and sharing through bidding for priority selection and/or de-selection of localized media selection and playback. They will have significant value in the digital media, mobile, wireless and location based markets. Yet, for video sharing in this context, enormous challenges still have to be overcome to fully realize anytime anywhere video browsing and publishing services for diverse multimedia-ready mobile devices. First, video capturing and uploading operations are both computation-intensive and bandwidth-hungry. Without a well-designed video processing/ compression algorithm, a mobile user will suffer from the short battery life and excessive mobile data volume. Second, the core enabler for location-based applications, GPS, incurs very high energy cost, which can easily cause complete battery drain within a few hours. It coverage is also confined to open outdoor areas, and the indoor signal reception can be very poor. It is necessary to examine the use of other sensors in today's mobile devices (e.g., WiFi, accelerometers, orientation sensors) together with GPS to obtain more accurate and continuous location information. In this project, a multidisciplinary team involving researchers from SFU and engineers from the company will be assembled to examine the above challenges and develop effective solutions. We will work closely to ensure that the research outcome are theoretically sound and also reflect the latest advances in mobile video capturing and sharing. Our video processing and location estimation algorithms are to be developed based on the realistic data and platforms provided by the company and will be tested with prototype implementation. As such, the outcome from the project can be easily integrated into the productline of the company.

Related Projects

Machine-to-Machine (M2M) networks have recently attracted significant attention from both industry and academia. Prominent examples are vehicular communication networks, which enable continuous status monitoring of a massive number of on-road vehicle... More ...