Abstract
We address the problem of robust estimation of motion and structure parameters, which describe an observer’s translation, rotation, and environmental layout (i.e. the relative depth of visible 3-d points) from noisy time-varying optical flow. Allowable observer motions include a moving vehicle and a broad class of robot arm motions. We assume the observer is a camera rigidly attached to the moving vehicle or robot arm, which moves along a smooth trajectory in a stationary environment. As the camera moves it acquires images at some reasonable sampling rate (say 30 images per second). Given a sequence of such images we analyze them to recover the camera’s motion and depth information for various surfaces in the environment. As the camera moves, with respect to some 3-d environmental point, the relative 3-d velocity that occurs is mapped (under perspective projection) onto the camera’s image plane as 2-d image motion. Optical flow or image velocity is an infinitesimal approximation to this image motion. Since the camera moves relative to a scene we can compute image velocity fields at each time. Given the observer’s translation, \(\vec U\), and rotation, \(\vec \omega \), and the coordinates of a 3-d point, \(\vec P\), a non-linear equation that relates these parameters to the 2-d image velocity, \(\vec \upsilon \), at image point \(\vec Y\), where \(\vec Y\) is the perspective projection of \(\vec P\), is as follows [10]:
where \({\vec \upsilon _T} \) and \({\vec \upsilon _R}\) are the translational and rotational components of image velocity:
and
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References
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Barron, J.L., Eagleson, R. (1997). Computation of time-varying motion and structure parameters from real image sequences. In: Solina, F., Kropatsch, W.G., Klette, R., Bajcsy, R. (eds) Advances in Computer Vision. Advances in Computing Science. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6867-7_19
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DOI: https://doi.org/10.1007/978-3-7091-6867-7_19
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