This Article 
 Bibliographic References 
 Add to: 
Focus-of-Attention from Local Color Symmetries
July 2004 (vol. 26 no. 7)
pp. 817-830

Abstract—In this paper, a continuous valued measure for local color symmetry is introduced. The new algorithm is an extension of the successful gray value-based symmetry map proposed by Reisfeld et al. The use of color facilitates the detection of focus points (FPs) on objects that are difficult to detect using gray-value contrast only. The detection of FPs is aimed at guiding the attention of an object recognition system; therefore, FPs have to fulfill three major requirements: stability, distinctiveness, and usability. The proposed algorithm is evaluated for these criteria and compared with the gray value-based symmetry measure and two other methods from the literature. Stability is tested against noise, object rotation, and variations of lighting. As a measure for the distinctiveness of FPs, the principal components of FP-centered windows are compared with those of windows at randomly chosen points on a large database of natural images. Finally, usability is evaluated in the context of an object recognition task.

[1] J.Y. Aloimonos, I. Weiss, and A. Bandyopadhyay, Active Vision Int'l J. Computer Vision, vol. 1, pp. 334-356, 1987.
[2] H. Asada and M. Brady, The Curvature Primal Sketch IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 8, no. 1, pp. 2-14, 1986.
[3] G. Backer, B. Mertsching, and M. Bollmann, Data and Model-Driven Gaze Control for an Active-Vision System IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 12, pp. 1415-1429, Dec. 2001.
[4] R. Bajcsy and M. Campos, Active and Exploratory Perception Computer Vision, Graphics, and Image Processing: Image Understanding, vol. 56, no. 1, pp. 31-40, 1992.
[5] C. Bauckhage, G.A. Fink, G. Heidemann, N. Jungclaus, F. Kummert, S. Posch, H. Ritter, G. Sagerer, and D. Schlüter, Towards an Image Understanding Architecture for a Situated Artificial Communicator Pattern Recognition and Image Analysis, vol. 9, no. 4, pp. 542-550, 1999.
[6] P. R. Beaudet, Rotationally Invariant Image Operators Proc. Fourth Int'l Joint Conf. Pattern Recognition, pp. 579-583, 1978.
[7] E. Braun, G. Heidemann, H. Ritter, and G. Sagerer, A Multi-Directional Multiple Path Recognition Scheme for Complex Objects Pattern Recognition Letters, special issue on Pattern Recognition in Practice VI, June 1999.
[8] S. Bres and J.M. Jolion, Detection of Interest Points for Image Indexation Proc. Third Int'l Conf. Visual Information Systems, Visual '99, pp. 424-434, 1999.
[9] V. Bruce and M. Morgan, Violation of Symmetry and Repetition in Visual Pathways Perception, vol. 4, pp. 239-249, 1975.
[10] K. Brunnström, J.-O. Eklundh, and T. Uhlin, Active Fixation for Scene Exploration Int'l J. Computer Vision, vol. 17, pp. 137-162, 1996.
[11] C.-H. Chen, J.-S. Lee, and Y.-N. Sun, Wavelet Transformation for Gray-Level Corner Detection Pattern Recognition, vol. 28, no. 6, pp. 853-861, 1995.
[12] J.C. Cottier, Extraction et Appariements Robustes des Points d'Intérêt de Deux Images nonÉtalonnées technical report, LIFIA-IMAG-INRIA, Rhone-Alpes, 1994.
[13] J.L. Crowley, P. Bobet, and M. Mesrabi, Camera Control for an Active Camera Head Pattern Recognition and Artificial Intelligence, J. L. Crowley, P. Stelmaszyk, T. Skordas, and P. Puget, vol. 7, no. 1, 1993.
[14] I. Daubechies, Orthonormal Bases of Compactly Supported Wavelets Comm. Pure and Applied Math., vol. 41, pp. 909-996, 1988.
[15] L. Dreschler and H.-H. Nagel, Volumetric Model and 3D Trajectory of a Moving Car Derived from Monocular TV Frame Sequences of a Street Scene Computer Graphics and Image Processing, vol. 20, pp. 199-228, 1982.
[16] W. Förstner, A Framework for Low Level Feature Extraction Proc. Third European Conf. Computer Vision, pp. 383-394, 1994.
[17] W.T. Freeman and E.H. Adelson, "The Design and Use of Steerable Filters," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, pp. 891-906, 1991.
[18] P.J.B. Hancock, R.J. Baddeley, and L.S. Smith, The Principal Components of Natural Images Network, vol. 3, pp. 61-70, 1992.
[19] U. Handmann, T. Kalinke, C. Tzomakas, M. Werner, and W. v. Seelen, An Image Processing System for Driver Assistance Image and Vision Computing, vol. 18, no. 5, pp. 367-376, 2000.
[20] R.M. Haralick and L.G. Shapiro, Computer and Robot Vision, vol. 2, 1993.
[21] C. Harris and M. Stephens, A Combined Corner and Edge Detector Proc. Fourth Alvey Vision Conf., pp. 147-151, 1988.
[22] G. Heidemann, Ein Flexibel Einsetzbares Objekterkennungssystem auf der Basis Neuronaler Netze PhD thesis, Infix, DISKI 190, Univ. Bielefeld, Technische Fakultät, 1998.
[23] G. Heidemann, D. Lücke, and H. Ritter, A System for Various Visual Classification Tasks Based on Neural Networks Proc. 15th Int'l Conf. Pattern Recognition, A. Sanfeliu et al., eds., vol. I, pp. 9-12, 2000.
[24] G. Heidemann, T.W. Nattkemper, and H. Ritter, Farbe und Symmetrie für die datengetriebene Generierung prägnanter Fokuspunkte Proc. Fourth Workshop Farbbildverarbeitung, V. Rehrmann, ed., pp. 65-71, 1998.
[25] G. Heidemann and H. Ritter, Combining Multiple Neural Nets for Visual Feature Selection and Classification Proc. Ninth Int'l Conf. Artificial Neural Networks, pp. 365-370, 1999.
[26] G. Heidemann and H. Ritter, Efficient Vector Quantization Using the WTA-Rule with Activity Equalization Neural Processing Letters, vol. 13, no. 1, pp. 17-30, 2001.
[27] F. Heitger, L. Rosenthaler, R. von der Heydt, E. Peterhans, and O. Kübler, Simulation of Neural Contour Mechanism: From Simple to End-Stopped Cells Vision Research, vol. 32, no. 5, pp. 963-981, 1992.
[28] R. Horaud, F. Veillon, and T. Skordas, Finding Geometric and Relational Structures in an Image Proc. First European Conf. Computer Vision, pp. 374-384, 1990.
[29] A.S. Householder, The Theory of Matrices in Numerical Analysis. New York: Dover Publications, 1964.
[30] L. Itti, C. Koch, and E. Niebur, “A Model for Saliency-Based Visual Attention for Rapid Scene Analysis,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 11, pp. 1,254-1,259, Nov. 1998.
[31] T. Kalinke and W. von Seelen, Entropie als Maßdes Lokalen Informationsgehalts in Bildern zur Realisierung einer Aufmerksamkeitssteuerung Mustererkennung, B. Jähne, P. Geißler, H. Haußecker, and F. Hering, eds., pp. 627-634, Heidelberg: Springer Verlag, 1996.
[32] L. Kaufman and W. Richards, Spontaneous Fixation Tendencies for Visual Forms Perception and Psychophysics, vol. 5, no. 2, pp. 85-88, 1969.
[33] L. Kitchen and A. Rosenfeld, Gray-Level Corner Detection Pattern Recognition Letters, vol. 1, pp. 95-102, 1982.
[34] J.J. Koenderink and A.J. van Doorn, Representation of Local Geometry in the Visual System Biological Cybernetics, vol. 55, pp. 367-375, 1987.
[35] R. Laganiére, Morphological Corner Detection Proc. Sixth Int'l Conf. Computer Vision, pp. 280-285, 1998.
[36] J.-S. Lee, Y.-N. Sun, and C.-H. Chen, "Multiscale Corner Detection by Using Wavelet Transform," IEEE Trans. Image Processing, vol. 4, no. 1, pp. 100-104, 1995.
[37] T. Lindeberg, Detecting Salient Blob-Like Image Structures and Their Scales with a Scale-Space Primal Sketch: A Method for Focus-of-Attention Int'l J. Computer Vision, vol. 11, no. 3, pp. 283-318, 1993.
[38] T. Lindeberg, Scale-Space Theory: A Basic Tool for Analysing Structures at Different Scales J. Applied Statistics, vol. 21, no. 2, pp. 224-270, 1994.
[39] P.J. Locher and C.F. Nodine, Symmetry Catches the Eye Eye Movements: From Physiology to Cognition, A. Levy-Schoen and J.K. O'Reagan, eds., pp. 353-361, B.V. (North Holland): Elsevier Science, 1987.
[40] J. Maintz and M. Viergever, A Survey of Medical Image Registration Medical Image Analysis, vol. 2, no. 1, pp. 1-36, 1998.
[41] S. Mallat, A Wavelet Tour of Signal Processing. Academic Press, 1998.
[42] G. Medioni and Y. Yasumoto, Corner Detection and Curve Representation Using Cubic B-Splines Computer Vision, Graphics, and Image Processing, vol. 39, pp. 267-278, 1987.
[43] B. Moghaddam and A. Pentland, “Probabilistic Visual Learning for Object Representation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 696-710, July 1997.
[44] H.P. Moravec, Towards Automatic Visual Obstacle Avoidance Proc. Fifth Int'l Joint Conf. Artificial Intelligence, pp. 584-587, 1977.
[45] H. Murase and S.K. Nayar, Visual Learning and Recognition of 3-D Objects from Appearance Int'l J. Computer Vision, vol. 14, pp. 5-24, 1995.
[46] T.W. Nattkemper, Untersuchung und Erweiterung eines Ansatzes zur modellfreien Aufmerksamkeitssteuerung durch lokale Symmetrien in einem Computer Vision System master's thesis, Technische Fakultät, Bielefeld Univ., Jan. 1997.
[47] S.A. Nene, S.K. Nayar, and H. Murase, Columbia Object Image Library: COIL-100 Technical Report CUCS-006-96, Dept. of Computer Science, Columbia Univ., 1996.
[48] Art Explosion®Photo Gallery, Nova Development Corp., year?
[49] S. Palmer, The Psychology of Perceptual Organization: A Transformational Approach Human and Machine Vision, J. Beck, B. Hope, and A. Rosenfeld, eds., Academic Press, 1983.
[50] C.M. Privitera and L.W. Stark, “Algorithms for Defining Visual Regions-of-Interest: Comparison with Eye Fixations,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 9, pp. 970-982, Sept. 2000.
[51] R.P.N. Rao and D.H. Ballard, An Active Vision Architecture Based on Iconic Representations Artificial Intelligence, vol. 78, pp. 461-505, 1995.
[52] R.P.N. Rao, G.J. Zelinsky, M.M. Hayhoe, and D.H. Ballard, Modeling Saccadic Targeting in Visual Search Advances in Neural Information Processing Systems 8, D. Touretzky, M. Mozer, and M. Hasselmo, eds., MIT Press, 1995.
[53] D. Reisfeld, H. Wolfson, and Y. Yeshurun, Context-Free Attentional Operators: The Generalized Symmetry Transform Int'l J. Computer Vision, vol. 14, pp. 119-130, 1995.
[54] G. Rickheit and I. Wachsmuth, Situated Artificial Communicators Artificial Intelligence Rev., vol. 10, pp. 165-170, 1996.
[55] T.D. Sanger, Optimal Unsupervised Learning in a Single-Layer Linear Feedforward Neural Network Neural Networks, vol. 2, pp. 459-473, 1989.
[56] C. Schmid and R. Mohr, “Local Grayvalue Invariants for Image Retrieval,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 5, pp. 530-535, May 1997.
[57] C. Schmid, R. Mohr, and C. Bauckhage, Evaluation of Interest Point Detectors Int'l J. Computer Vision, vol. 37, no. 2, pp. 151-172, 2000.
[58] E. Shilat, M. Werman, and Y. Gdalyahu, "Ridge's Corner Detection and Correspondence," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 976-981, 1997.
[59] A. Shokoufandeh, I. Marsic, and S.J. Dickinson, View-Based Object Recognition Using Saliency Maps Image and Vision Computing, vol. 17, pp. 445-460, 1999.
[60] S. Smith and J. Brady, SUSAN A New Approach to Low Level Image Processing Int'l J. Computer Vision, vol. 23, no. 1, pp. 45-78, 1997.
[61] J. Steil, G. Heidemann, J. Jockusch, R. Rae, N. Jungclaus, and H. Ritter, Guiding Attention for Grasping Tasks by Gestural Instruction: The GRAVIS-Robot Architecture Proc. IEEE/RSJ Int'l Conf. Intelligent Robots and Systems, 2001.
[62] Q. Tian, N. Sebe, M.S. Lew, E. Loupias, and T.S. Huang, Image Retrieval Using Wavelet-Based Salient Points J. Electronic Imaging, vol. 10, no. 4, pp. 835-849, 2001.
[63] C. Tomasi and T. Kanade, Detection and Tracking of Point Features Technical Report CMU-CS-91-132, Carnegie Mellon Univ., Pittsburgh, 1991.
[64] T. Tuytelaars and L. van Gool, Content-Based Image Retrieval Based on Local Affinely Invariant Regions Proc. Third Int'l Conf. Visual Information Systems, pp. 493-500, 1999.
[65] H. Zabrodsky, S. Peleg, and D. Avnir, "Symmetry as a Continuous Feature," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, pp. 1,154-1,166, 1995.
[66] Z. Zheng, H. Wang, and W. Teoh, Analysis of Gray Level Corner Detection Pattern Recognition Letters, vol. 20, pp. 149-162, 1999.
[67] B. Zitova, J. Kautsky, G. Peters, and J. Flusser, Robust Detection of Significant Points in Multi-Frame Images Pattern Recognition Letters, vol. 20, pp. 199-206, 1999.

Index Terms:
Focus-of-attention, color vision, symmetry, saliency maps, object recognition.
Gunther Heidemann, "Focus-of-Attention from Local Color Symmetries," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 7, pp. 817-830, July 2004, doi:10.1109/TPAMI.2004.29
Usage of this product signifies your acceptance of the Terms of Use.