Multi-Frame motion deblurring of video using the natural oscillatory motion of dexterous legged robots

Gultekin, Gokhan Koray
Saranlı, Afşar
Motion blur is a common problem for machine vision applications in legged mobile robotic platforms. Due to the oscillatory walking nature of these platforms, the cameras on them experience disturbances so that most of the captured frames are motion blurred. Motion blur results in loss of information in individual image frames and therefore makes single-frame deblurring an ill-posed problem. The variation in the magnitude of motion blur in consecutive video frames can be exploited to better restore these frames by combining the information available in them. The authors focus on the multi-frame image deblurring problem and propose a promising method to achieve this information fusion especially when the video is corrupted by non-linear blur, such as the case in legged mobile robots. The authors present the theory and results obtained on a realistic motion-blur dataset collected on a representative robotic platform. These results are also compared with a leading single-frame deblurring method and show improvement in particular for video corrupted by linear and non-linear motion blur.


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Dexterous legged robots are agile platforms that can move on variable terrain at high speeds. The locomotion of these legged platforms causes oscillations of the robot body which become more severe depending on the surface and locomotion speed. Camera sensors mounted on such platforms experience the same disturbances, hence resulting in motion blur. This is a corruption of the image and results in loss of information which in turn causes degradation or loss of important image features. Most of the studies i...
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Motion blur is a common problem that produces blurry images with inevitable information loss and unpleasant visual quality. Relative motion between scene and image recording device during exposure time causes the motion blur. This artifact degrades the human perceptual quality and also challenges subsequent computer vision applications. Most of the studies in the literature assume uniform blur present in the image and focuses on removing motion blur with non-blind deconvolution algorithms because of their l...
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Citation Formats
G. K. Gultekin and A. Saranlı, “Multi-Frame motion deblurring of video using the natural oscillatory motion of dexterous legged robots,” IET IMAGE PROCESSING, pp. 1502–1508, 2019, Accessed: 00, 2020. [Online]. Available: