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| Javier Cabrera, Peter Meer, "Unbiased Estimation of Ellipses by Bootstrapping," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 7, pp. 752-756, July, 1996. | |||
| BibTex | x | ||
| @article{ 10.1109/34.506797, author = {Javier Cabrera and Peter Meer}, title = {Unbiased Estimation of Ellipses by Bootstrapping}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {18}, number = {7}, issn = {0162-8828}, year = {1996}, pages = {752-756}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.506797}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - Unbiased Estimation of Ellipses by Bootstrapping IS - 7 SN - 0162-8828 SP752 EP756 EPD - 752-756 A1 - Javier Cabrera, A1 - Peter Meer, PY - 1996 KW - Implicit models KW - curve fitting KW - bootstrap KW - low-level processing. VL - 18 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
Abstract—A general method for eliminating the bias of nonlinear estimators using bootstrap is presented. Instead of the traditional mean bias we consider the definition of bias based on the median. The method is applied to the problem of fitting ellipse segments to noisy data. No assumption beyond being independent identically distributed (i.i.d.) is made about the error distribution and experiments with both synthetic and real data prove the effectiveness of the technique.
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