Perception, hence the usage of visual sensors is indispensable in mobile and autonomous
robotics. Visual sensors such as cameras, rigidly mounted on a robot frame are the most
common usage scenario. In this case, the motion of the camera due to the motion of the
moving platform as well as the resulting shocks or vibrations causes a number of distortions
on video frame sequences. Two most important ones are the frame-to-frame changes of the
line-of-sight (LOS) and the presence of motion blur in individual frames. The latter of these
two, namely motion blur plays a particularly dominant role in determining the performance of
many vision algorithms used in mobile robotics. It is caused by the relative motion between
the vision sensor and the scene during the exposure time of the frame. Motion blur is clearly
an undesirable phenomenon in computer vision not only because it degrades the quality of
images but also causes other feature extraction procedures to degrade or fail. Although there
are many studies on feature based tracking, navigation, object recognition algorithms in the
computer vision and robotics literature, there is no comprehensive work on the effects of
motion blur on different image features and their extraction.
In this thesis, a survey of existing models of motion blur and approaches to motion deblurring is presented. We review recent literature on motion blur and deblurring and we focus our
attention on motion blur induced degradation of a number of popular feature detectors. We
investigate and characterize this degradation using video sequences captured by the vision
system of a mobile legged robot platform. Harris Corner detector, Canny Edge detector and
Scale Invariant Feature Transform (SIFT) are chosen as the popular feature detectors that are
most commonly used for mobile robotics applications. The performance degradation of these
feature detectors due to motion blur are categorized to analyze the effect of legged locomotion
on feature performance for perception. These analysis results are obtained as a first step
towards the stabilization and restoration of video sequences captured by our experimental
legged robotic platform and towards the development of motion blur robust vision system.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12612475/index.pdf |
| Date | 01 September 2010 |
| Creators | Uzer, Ferit |
| Contributors | Saranli, Afsar |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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