TY - CHAP
T1 - A Hybrid Approach to Domino Portrait Generation
AU - Cambazard, Hadrien
AU - Horan, John
AU - O’Mahony, Eoin
AU - O’Sullivan, Barry
N1 - Publisher Copyright:
Copyright © 2008, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2008
Y1 - 2008
N2 - A domino portrait is an approximation of an image using a given number of sets of dominoes. This problem was first stated in 1981. Domino portraits have been generated most often using integer linear programming techniques that provide optimal solutions, but these can be slow and do not scale well. We demonstrate a new approach that overcomes these limitations and provides high quality portraits. Our software combines techniques from operations research, artificial intelligence, and computer vision. Starting from a randomly generated template of blank domino shapes, a subsequent optimal placement of dominoes can be achieved in constant time when the problem is viewed as a minimum cost flow. The domino portraits one obtains are good, but not as visually attractive as optimal ones. Combining techniques from computer vision and local search we can improve our portraits to be visually indistinguishable from those generated optimally.
AB - A domino portrait is an approximation of an image using a given number of sets of dominoes. This problem was first stated in 1981. Domino portraits have been generated most often using integer linear programming techniques that provide optimal solutions, but these can be slow and do not scale well. We demonstrate a new approach that overcomes these limitations and provides high quality portraits. Our software combines techniques from operations research, artificial intelligence, and computer vision. Starting from a randomly generated template of blank domino shapes, a subsequent optimal placement of dominoes can be achieved in constant time when the problem is viewed as a minimum cost flow. The domino portraits one obtains are good, but not as visually attractive as optimal ones. Combining techniques from computer vision and local search we can improve our portraits to be visually indistinguishable from those generated optimally.
UR - https://www.scopus.com/pages/publications/85167435002
M3 - Chapter
AN - SCOPUS:85167435002
T3 - Proceedings of the 23rd AAAI Conference on Artificial Intelligence, AAAI 2008
SP - 1874
EP - 1875
BT - Proceedings of the 23rd AAAI Conference on Artificial Intelligence, AAAI 2008
PB - AAAI Press
T2 - 23rd AAAI Conference on Artificial Intelligence, AAAI 2008
Y2 - 13 July 2008 through 17 July 2008
ER -