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N. Kiryati, A.M. Bruckstein, "What's in a Set of Points? (Straight Line Fitting)," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 4, pp. 496500, April, 1992.  
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@article{ 10.1109/34.126810, author = {N. Kiryati and A.M. Bruckstein}, title = {What's in a Set of Points? (Straight Line Fitting)}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {14}, number = {4}, issn = {01628828}, year = {1992}, pages = {496500}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.126810}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  What's in a Set of Points? (Straight Line Fitting) IS  4 SN  01628828 SP496 EP500 EPD  496500 A1  N. Kiryati, A1  A.M. Bruckstein, PY  1992 KW  parameter estimation; statistical analysis; least squares approximations; straight line fitting; parameter space computational approach; optimality criteria; Hough transform; M estimators; curve fitting; least squares approximations; parameter estimation; statistical analysis; transforms VL  14 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
The problem of fitting a straight line to a planar set of points is reconsidered. A parameter space computational approach capable of fitting one or more lines to a set of points is presented. The suggested algorithm handles errors in both coordinates of the data points, even when the error variances vary between coordinates and among points and can be readily made robust to outliers. The algorithm is quite general and allows line fitting according to several useful optimality criteria to be performed within a single computational framework. It is observed that certain extensions of the Hough transform can be turned to be equivalent to wellknown M estimators, thus allowing computationally efficient approximate M estimation.
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