SenseCoding: accelerometer-assisted motion estimation for efficient video encoding

ABSTRACT

Accelerometers have appeared on many camcorders, cameras and mobile phones. We present algorithms that estimate camera movement from accelerometer readings and apply the estimation to significantly improve the compute-intense motion estimation in video encoding. We have implemented a working prototype that simultaneously captures video and three-axis acceleration data. The video is then compressed with a reference MPEG-2 encoder, modified to incorporate the accelerometer readings to assist motion estimation. Our experimental data shows a two to three times speed improvement for the entire encoding process, in comparison with full search.

REFERENCES

• 1: Guang-ming Hong, Ahmad Rahmati, Ye Wang, and Lin Zhong, "SenseCoding: Accelerometer-assisted motion estimation for efficient video encoding," Joint Technical Report, School of Computing, National University of Singapore and Dept. of Electrical & Computing Engineering, Rice University. http://www.recg.org/publications/hong08sensecoding.pdf
• 2: Camera Calibration Toolbox for Matlab, http://www.vision.caltech.edu/bouguetj/calib_doc/
• 3: Rice Orbit Sensor Platform, http://www.recg.org/orbit/
• 4: MPEG2 Test Model 5 (TM5), http://www.mpeg.org/MPEG/MSSG/tm5/

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.1 Multimedia Information Systems
          Subjects: Video (e.g., tape, disk, DVI)

General Terms:
Algorithms, Design, Performance

Keywords:
accelerometer, motion estimation, mpeg-2, video encoding