Digital geometry image analysis for medical diagnosis

Proceedings of the ACM Symposium on Applied Computing

Volumn 1, Issue , 2006, Pages 217-221

  Fang, Jiandong ^a   Fang, Shiaofen ^a   Huang, Jeffrey ^a   Tuceryan, Mihran ^a  

^a IN 46202 USA   (United States)

Author keywords

3D facial analysis; Classifier; Digital geometry; Fetal alcohol syndrome; Medical diagnosis; Pattern recognition

Indexed keywords

DATA ACQUISITION; DATABASE SYSTEMS; DIAGNOSIS; FEATURE EXTRACTION; PATIENT MONITORING; PATTERN RECOGNITION;

3D FACIAL ANALYSIS; DIGITAL GEOMETRY; FETAL ALCOHOL SYNDROME; POLYGON MESH SURFACES;

IMAGE ANALYSIS;

EID: 33751050134     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1141277.1141327     Document Type: Conference Paper

References (22)

1. Arman, F., and J. K. Aggarwal (1993). "Model-based object recognition in dense-range images - a review." ACM Computing Surveys 25(1): 5-43.
2. th Annual Joint Symposium on Neural Computation, Pasadena, CA. May 17, 1997.
3. Besl, P. and R. C. Jain (1985). "Three-dimensional Object Recognition." ACM Computing Surveys 17(1): 75-145.
4. Besl, P. J. and A. Jain (1988). "Segmentation through variable-order surface fitting." IEEE Transaction on Pattern Analysis and Machine Intelligence 10(2): 167-192.
5. Besl, P. and N. McKay (1992), "A Method for Registration of 3D Shapes", IEEE Trans. PAMI, vol. 14, no. 2, 239-256.
6. Beumier, C. and M. Acheroy (2000), Automatic 3D face authentication, Image & Vision Computing, 18(4), 315-321.
7. Comon, P. (1994). "Independent Component Analysis: A New Concept?" Signal Processing 36: 287-314.
8. Gordon, G. (1991), Face recognition based on depth maps and surface curvature, in SPIEproc. on Geometric Method in Computer Vision, vol.1570, pp.234-247.
9. Haykin, S, Neural Networks - A Comprehensive Foundation, 2nd ed. Prentice-Hall, 1998.
10. Hu, M. K. (1962). "Visual Pattern Recognition by Moment Invariants." IRE Trans. on Information Theory 8: 179-187.
11. Huang, J. and H. Wechsler, Visual Routines for Eye Location Using Learning and Evolution, IEEE Trans. on Evolutionary Computation (EC), 4 (1), pp.73-82, 2000.
12. Jain, A. K. and R. Hoffman (1988). "Evidence based recognition of 3D objects." IEEE Transaction on Pattern Analysis and Machine Intelligence 10(6): 783-802.
13. Jolliffee, I.T., "Principal Component Analysis", New York, Springer Verlag, 1986.
14. Meyer, M., M. Desbrun, P. Schroder, and A. Barr, "Discrete Differential Geometry Operators for Triangulated 2-Manifolds", VisMath 02, Berlin (Germany), 2002.
15. Powell, M., "An efficient method for finding the minimum of a function of several variables without calculating derivatives", Computer Journal, vol. 7, 155-162, 1964.
16. Schroder, P. and W. Sweldens, "Digital Geometry Processing". In Sixth Annual Symposium on Frontiers of Engineering, 41-44, 2001.
17. Swets, D. L. and J. Weng (1996). "Using Discriminant Eigenfeatures for Image Retrieval." IEEE Transactions on Pattern Analysis and Machine Intelligence 18(8): 831-836.
18. Tanaka, H.T., M. Ikeda, and H. Chiaki (1998), Curvature-base face surface recognition using spherical correlation - rincipal directions for curved object recognition, Proc. Int. Conf. on Automatic Face Gesture Recognition, 372-377.
19. Taubin, G. (2000). "Geometric Signal Processing on Polygonal Meshes." Eurographics 2000, State of the An Report (STAR), INTERLAKEN, Switzerland.
20. Turk, M. and A. Pentland (1991). "Eigenfaces for Recognition." J. of Cognitive Neuroscience 3(1): 71-86.
21. Vladimir N. Vapnik, The Statisitcal Learning Theory. Springer, 1998.
22. Zhao, C., D. Zhao, et al. (1996). "Simplified Gaussian and Mean Curvatures to Range Image Segmentation." Proceedings of the 1996 International Conference on Pattern Recognition (ICPR' 96) IEEE.