Parallel computing

Publications related to parallel computing.

  1. T. Lourens and E. I. Barakova. My Sparring Partner is a Humanoid Robot -A parallel framework for improving social skills by imitation [1646 KB pdf]. In J. R. Alvarez, editor, IWINAC 2009, number 5602 in Lecture Notes in Computer Science, pages 344-352, Santiago de Compostella, Spain, June 2009. Springer-verlag.


    This paper presents a framework for parallel tracking of human hands and faces in real time, and is a partial solution to a larger project on human-robot interaction which aims at training autistic children using a humanoid robot in a realistic non-restricted environment. In addition to the framework, the results of tracking different hand waving patterns are shown. These patterns provide an easy to understand profile of hand waving, and can serve as the input for a classification algorithm.

  2. T. Lourens, N. Petkov, and P. Kruizinga. Large scale natural vision simulations [342 KB pdf]. Future Generation Computer Systems, Issue: High Performance Computing and Networking (HPCN), 10:351-358, June 1994.


    A computationally intensive approach to pattern recognition in images is developed and applied to face recognition. Similarly to previous work, we compute functional inner products of a two-dimensional input signal (image) with a set of two-dimensional Gabor functions which fit the receptive fields of simple cells in the primary visual cortex of mammals. The proposed model includes non-linearities, such as thresholding, orientation competition, and lateral inhibition. The output of the model is a set of cortical images each ofwhich contains only edge lines of a particular orientation in a particular light-to-dark transition direction. In this way the information of the original image is split into different channels. The cortical images are used to compute a lower-dimension space representation for object recognition. The method was implemented on the Connection Machine CM-5 and achieved a recognition rate of 97% when applied to a large database of face images.

  3. N. Petkov, P. Kruizinga, and T. Lourens. Face Recognition on the Connection Machine CM-5 [519 KB pdf]. In G.R. Joubert, D. Trystram, F.J. Peters, and D.J. Evans, editors, Parallel Computing: Trends and Applications, Proceedings of the International Conference on Parallel Computing ’93, volume 9 of Advances in Parallel Computing, pages 185-192, Grenoble, France, Sept. 7-10, 1993. Elsevier Science Publishers B.V. Amsterdam.


    A biologically motivated compute intensive approach to computer vision is developed and applied to the problem of face recognition. The approach is based on the use of two-dimensional Gabor functions that t the receptive elds of simple cells in the primary visual cortex of mammals. A descriptor set that is robust against translations is extracted and used for a search in an image database. The method was applied on a database of 205 face images of 30 persons and a recognition rate of 94% was achieved. The nal version of the paper will report on the results obtained by applying a set of 1024 Gabor functions on a database of 1000 face images of 150 persons and on the implementation on a Connection Machine CM-5 parallel supercomputer to be installed at our university until the end of 1992.

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.