Fondazione Bruno Kessler - Technologies of Vision

contains material from
Template Matching Techniques in Computer Vision: Theory and Practice
Roberto Brunelli 2009 John Wiley & Sons, Ltd


[1]   CM Bishop. Pattern Recognition and Machine Learning. Springer, 2007.

[2]   RO Duda, PE Hart, and DG Stork. Pattern Classification. Wiley, 2nd edition, 2000.

[3]   DA Forsyth and J Ponce. Computer Vision: A Modern Approach. Prentice Hall, 2002.

[4]   K Fukunaga. Statistical Pattern Recognition. Academic Press, 2nd edition, 1990.

[5]   BK Horn. Robot Vision. The MIT Press, 1986.

[6]   D Marr. Vision. W.H. Freeman, 1982.

[7]   Mathematical Society of Japan. Encyclopedic Dictionary of Mathematics. MIT Press, 2 edition, 1993.

[8]   TK Moon and WC Stirling. Mathematical Methods and Algorithms for Signal Processing. Prentice-Hall, 2000.

[9]   AJ O’Toole, PJ Phillips, J Fang, J Ayyad, N Penard, and H Abdi. Face recognition algorithms surpass humans matching faces over changes in illumination. IEEE Trans. on Pattern Analysis and Machine Intelligence, 29(9):1642–1646, 2007.

[10]   A Papoulis. Probability, Random Variables and Stochastic Processes. McGraw-Hill, 1965.

[11]   WH Press, SA Teukolsky, WT Vetterling, and BP Flannery. Numerical Recipes. Cambridge University Press, 3rd edition, 2007.

[12]   P Sinha, B Balas, Y Ostrovsky, and R Russell. Face recognition by humans: Nineteen results all computer vision researchers should know about. Proceedings of the IEEE, 94:1948–1962, 2006. Face Recognition.