DocumentCode :
154127
Title :
Motion aware motion invariance
Author :
McCloskey, Scott ; Muldoon, Kelly ; Venkatesha, Sharath
Author_Institution :
Honeywell ACS Labs., Golden Valley, MN, USA
fYear :
2014
fDate :
2-4 May 2014
Firstpage :
1
Lastpage :
9
Abstract :
We address motion de-blurring using a computational camera that captures an image while the stabilizing optical element moves in a modified Canon IS lens. Our work builds on that of Levin et al. [11], who introduce parabolic motion as a means of achieving invariance to unknown subject velocity in an a priori known direction. While the previous work addresses a specific scenario - exact knowledge of motion orientation and a uniform, symmetric prior on its magnitude - we generalize this to address scenarios where the motion of objects in the scene or the camera itself are known to various extents. We describe a motion invariant camera based on an off-the-shelf lens, and show how its motion and position sensors can be used to inform both the image capture and de-blurring. We demonstrate that our changes to motion invariance improve the quality of captured images in the case of both object and camera motion.
Keywords :
image capture; image motion analysis; image restoration; image sensors; photographic lenses; captured image quality improvement; computational camera; modified Canon IS lens; motion aware motion invariance; motion deblurring; motion invariant camera; motion sensor; object motion; off-the-shelf lens; optical element stabilisation; parabolic motion; position sensor; Acceleration; Cameras; ISO; Image sensors; Lenses; Noise; Sensors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Photography (ICCP), 2014 IEEE International Conference on
Conference_Location :
Santa Clara, CA
Type :
conf
DOI :
10.1109/ICCPHOT.2014.6831810
Filename :
6831810
Link To Document :
بازگشت