Comparison of view-based object recognition algorithms using realistic 3D models
Volker Blanz, Bernhard Schölkopf, H. Bülthoff, Christopher J. C. Burges, Vladimir N. Vapnik, Thomas R. Vetter · 1996
. Two view-based object recognition algorithms are compared: (1) a heuristic algorithm based on oriented filters, and (2) a support vector learning machine trained on low-resolution images of the objects. Classification performance is assessed using a high number of images generated by a computer graphics system under precisely controlled conditions. Training- and test-images show a set of 25 realistic threedimensional models of chairs from viewing directions spread over the upper half of the viewing sphere. The percentage of correct identification of all 25 objects is measured. in: C. von der Malsburg, W. von Seelen, J. C. Vorbruggen, & B. Sendhoff (eds.): Artificial Neural Networks --- ICANN'96. Springer Lecture Notes in Computer Science, Vol. 1112, Berlin, 1996, 251 --256 In computer vision, view--based models of object recognition have become more and more influential in recent years. Moreover, psychophysical evidence has been found for a view--based representation of objects in h...