A Real-Time Inertial Motion Blur Metric: Application to Frame Triggering Based Motion Blur Minimization

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2014-06-07

Author

Mutlu, Mehmet
Saranlı, Afşar
Saranlı, Uluç

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Mobile robots suffer from sensory data corruption due to body oscillations and disturbances. In particular, information loss on images captured with onboard cameras can be very high, and such loss may become irreversible or computationally costly to undo. In this paper, we propose a novel method to minimize average motion blur captured by such mobile visual sensors. To this end, we derive a motion blur metric (MMBM) that can be computed in real-time by using only inertial sensor measurements and validate it through comparisons with optic flow computations. The applicability of MMBM is illustrated through a motion blur minimizing system implemented on the SensoRHex hexapod robot by externally triggering an onboard camera based on MMBM values computed in real-time while the robot is walking straight on a flat surface. The resulting motion blur is compared to motion blur levels obtained with a regular, fixed frame-rate image acquisition schedule by both qualitative inspection and using a blind blur metric on captured images. MMBM based motion blur minimization system not only reduces average motion blur, but also avoids frames with extreme motion blur before an image gets corrupted by appropriately delaying the triggering of frame acquisition.

Subject Keywords

Automation & Control Systems, Robotics

URI

https://hdl.handle.net/11511/30501

DOI

https://doi.org/10.1109/icra.2014.6906926

Conference Name

IEEE International Conference on Robotics and Automation (ICRA)

Collections

Graduate School of Social Sciences, Conference / Seminar

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A Novel real-time inertial motion blur metric with applications to motion blur compensation / Mutlu, Mehmet; Saranlı, Afşar; Saranlı, Uluç; Department of Electrical and Electronics Engineering (2014) Mobile robots suffer from sensory data corruption due to body oscillations and motion disturbances. In particular, information loss in images captured with on board cameras can be very high, may become irreversible or computationally costly to compensate. In this thesis, a novel method to minimize average motion blur captured by such mobile visual sensors is proposed. To this end, an inertial sensor data based motion blur metric, MMBM, is derived. The metric can be computed in real time. Its accuracy is val...
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Citation Formats

M. Mutlu, A. Saranlı, and U. Saranlı, “A Real-Time Inertial Motion Blur Metric: Application to Frame Triggering Based Motion Blur Minimization,” presented at the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, PEOPLES R CHINA, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/30501.