Titlebook: Ellipse Fitting for Computer Vision; Implementation and A Kenichi Kanatani,Yasuyuki Sugaya,Yasushi Kanazawa Book 2016 Springer Nature Switz

genuine

较早

Geometric Fitting,describe a procedure for exactly minimizing the sum of squares from the data points, called the “geometric distance,” iteratively using the FNS procedure. Finally, we show how the accuracy can be further improved by a scheme called “hyperaccurate correction.”

影响深远

Coronary

Extension and Generalization,computing the fundamental matrix from two images and computing the homography between two planar surface images. They are both themselves indispensable tasks for 3-D scene analysis by computer vision. We show how they are computed by extending and generalizing the ellipse fitting procedure.

Thyroxine

Accuracy of Algebraic Fitting,ly applies to the fundamental matrix computation described in Section 7.1, we treat {itθ} and {itξ}{in{itga}} as {itn}-D vectors ({itn} = 6 for ellipse fitting, and {itn} = 9 for fundamental matrix computation) and do not use particular properties of ellipse fitting.

雀斑

Theoretical Accuracy Limit,hieve this bound up to higher order terms in {itσ}, meaning that these are all optimal with respect to covariance. As in Chapters 8 and 9, we treat {itθ} and {itξ}{in{itga}} as {itn}-D vectors for generality, and the result of this chapter applies to a wide variety of problems including the fundamental matrix computation described in Chapter 7.

Spartan

Interferons

Experiments and Examples, enforce the fit to be an ellipse in the presence of large noise and conclude that they do not have much practical value. Finally, we show some application examples of the ellipse-based 3-D computation described in Chapter 5.

匍匐前进

Book 2016applications. For this reason, the study of ellipse fitting began as soon as computers came into use for image analysis in the 1970s, but it is only recently that optimal computation techniques based on the statistical properties of noise were established. These include renormalization (1993), which

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