NDLI: Characterizing Depth Distortion under Different Generic Motions

Content Provider	Springer Nature Link
Author	Cheong, Loong Fah Xiang, Tao
Copyright Year	2001
Abstract	Given that errors in the estimates for the intrinsic and extrinsic camera parameters are inevitable, it is important to understand the behaviour of the resultant distortion in depth recovered under different motion-scene configurations. The main interest in this study is to look for generic motion type that can render depth recovery more robust and reliable. To this end, lateral and forward motions are compared both under calibrated and uncalibrated scenarios. For lateral motion, we found that although Euclidean reconstruction is difficult, ordinal depth information is obtainable; while for forward motion, depth information (even partial one) is difficult to recover. In the uncalibrated case, with fixed intrinsic parameters, the preceding statements still hold. However, if intrinsic parameter variations are allowed, then for lateral motion, depth relief can only be preserved locally. In general, lateral motion yields a distortion relationship that belongs to the projective transformation of a very simple type, while the distortion transformations for general motions including forward motion belong to the Cremona transformation. As an aside, we also provide an analysis of the distortion in the depth recovered using the least square procedure as compared to the epipolar reconstruction approach.
Starting Page	199
Ending Page	217
Page Count	19
File Format	PDF
ISSN	09205691
Journal	International Journal of Computer Vision
Volume Number	44
Issue Number	3
e-ISSN	15731405
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2001-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Artificial Intelligence (incl. Robotics) Computer Imaging, Graphics and Computer Vision Image Processing Automation and Robotics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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