2016 Art of the Portrait Conference: Day 1 (part 1)

by Matthew Innis |

James Gurney, a comfortable and educated speaker, keeps the audience in rapt attention during the opening hours of the first full day at the 18th The Art of the Portrait Conference.

I have had the good fortune to see many great speeches and demonstrations on the main stage during the many The Art of the Portrait conferences I have attended.  I remember fondly those times that Ray Kinstler and Michael Shane Neal, two eminent raconteurs, have entertained the audience and had them falling from their chairs with laughter;  when Rose Frantzen taught us how to put all of one’s energy into a painting;  or when Quang Ho taught us life’s philosophy with every stroke of his brush.  Those events, and so many more, have been wonderful, and I am glad that I have been there to experience them.  But with all deference to those people and what they offered to us all from that platform, the best pure presentation by far has got to be that given by James Gurney at this most recent conference.

There is a reason James Gurney is invited all around the world to address audiences of artists.  First and foremost, he knows his stuff.  But as important as that is, it takes much more than that to offer something truly special.  With the right blend of art, science, visual presentation, timing, and humor, the easy-going Gurney had the audience entranced from the very first word.

Gurney’s “Likeness and Character?” was a reprisal of the keynote speech he gave during the awards banquet of 2014, but with new imagery and more recent scientific support.  Primarily, the presentation dealt with the visual perception of the human face, how we register features and develop recognition, and how much more the exaggeration of features creates portraits that speak to us of the sitter than would any simple photograph.  With images from the internet and quotes from various studies, Gurney made the argument, and at the end of his presentation he shared a few videos of himself working from sitters who were either singing or talking, and how their constant movement engendered less exact but more lifelike portraits.

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A computer generated portrait made through a mathematical analysis of Rembrandt’s paintings. Math alone cannot make a Rembrandt.

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    Kakwirakeron Montour

    Great Article!

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