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Augmented Privacy with Virtual Humans

  • Chapter
Digital Human Modeling

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4650))

Abstract

Visual privacy is a sensitive subject because it literally deals with human private parts. It presents a bold challenge to the field of Computer Science. The goal of this study is to build a virtual human model for designing and evaluating visual privacy technologies before a security system is built. Given the available databases of anthropological models from CAESAR, 3D scanners and the physical parameters of human imaging systems, we simulate the scanning imagery data with the High Frequency Structure Simulator (HFSS). The proportion and template matching algorithms have been developed to find the human surface features from 3D scanning data. The concealed object detection algorithms are developed according to the wave intensity and surface characteristics. Then the privacy-aware rendering methods are evaluated by usability studies. This forward-thinking approach intends to transform the development of visual privacy technologies from device-specific and proprietary to device-independent and open source. It also advances privacy research from an ad-hoc problem-solving process to a systematic design process, enabling multi-disciplinary innovations in digital human modeling, computer vision, information visualization, and computational aesthetics.

The results of this study can be used in the privacy-aware imaging systems in airports and medical systems. They can also benefit the custom-fit products that are designed from personal 3D scanning data. Furthermore, our results can be used in the reconstruction of objects in digital archeology and medical imaging technologies such as virtual colonoscopy.

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References

  1. Laws, J., Cai, Y.: Feature Hiding in 3D Human Body Scans. Journal of Information Visualization 5(4) (2006), http://www.palgrave-journals.com/ivs/journal/v5/n4/abs/9500136a.html

  2. Laws, J., Cai, Y.: A Privacy Algorithm for 3D Human Body Scans. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2006. LNCS, vol. 3994, pp. 870–877. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  3. Cai, Y., et al.: Spatiotemporal data mining for tracking ocean objects. In: Proceedings of IEEE Space Mission Challenges to IT, Pasadena, CA (2006)

    Google Scholar 

  4. Cai, Y., et al.: Visual Transform for spatiotemporal data mining. Journal of Knowledge and Information Systems (to appear, 2007)

    Google Scholar 

  5. BodySearch imaging system, American Science and Engineering, Inc., 829 Middlesex Turnpike, Billerica, MA 01821

    Google Scholar 

  6. Secure 1000 imaging system, IRT Corporation, 6020 Cornerstone Court West, San Diego, CA 92121

    Google Scholar 

  7. McMakin, D.L., Sheen, D.M., Collins, H.D., Hall, T.E., Severtsen, R.H.: Wideband, millimeter-wave, holographic surveillance systems. In: EUROPTO International Symposium on Law Enforcement Technologies: Identification Technologies and Traffic Safety, Munich, FRG, SPIE, vol. 2092, pp. 131–141 (1995)

    Google Scholar 

  8. Sheen, D.M., McMakin, D.L., Collins, H.D.: Circular scanned millimeter-wave imaging system for weapon detection. In: EUROPTO International Symposium on Law Enforcement Technologies: Identification Technologies and Traffic Safety, Munich, FRG, SPIE, vol. 2092, pp. 122–130 (1995)

    Google Scholar 

  9. McMakin, D.L., Sheen, D.M., Collins, H.D., Hall, T.E., Smith, R.R.: Millimeter-wave, high-resolution, holographic surveillance system. In: EUROPTO International Symposium on Substance Identification Technologies, Innsbruck, Austria, SPIE, vol. 2092, pp. 525–535 (1993)

    Google Scholar 

  10. Sheen, D.M., McMakin, D.L., Collins, H.D., Hall, T.E.: Weapon detection using a wideband millimeter-wave linear array imaging technique. In: EUROPTO International Symposium on Substance Identification Technologies, Innsbruck, Austria, SPIE, vol. 2092, pp. 536–547 (1993)

    Google Scholar 

  11. Huguenin, G.R., Goldsmith, P.F., Deo, N.C., Walker, D.K.: Contraband Detection System. U. S. Patent 5, 073, 782 (1991)

    Google Scholar 

  12. Browne, J.: MM waves aid commercial applications. Microwaves and RF, 113–116 (July 1992)

    Google Scholar 

  13. Goodman, J.W.: Introduction to Fourier Optics. McGraw-Hill, New York

    Google Scholar 

  14. Soumekh, M.: Bistatic synthetic aperture radar inversion with application in dynamic object imaging. IEEE Transactions on Signal Processing 39(9), 2044–2055 (1991)

    Article  Google Scholar 

  15. Soumekh, M.: Fourier Array Imaging. Prentice-Hall, Englewood Cliffs (1994)

    MATH  Google Scholar 

  16. Anthropometry Resource (CAESAR), Final Report, vol. I: Summary, AFRL-HE-WP-TR-2002-0169, United States Air Force Research Laboratory, Human Effectiveness Directorate, Crew System Interface Division, 2255 H Street, Wright-Patterson AFB OH 45433-7022 and SAE International, 400 Commonwealth Dr., Warrendale, PA 15096

    Google Scholar 

  17. Bansal, M.: Analysis of curvature in genomic DNA, http://www.ibab.ac.in/bansal.htm

  18. Besl, P.J., Jain, R.C.: Three-dimensional object recognition. ACM Comput. Surveys 17(1), 75–145 (1985)

    Article  Google Scholar 

  19. Brady, M., Ponce, J., Yuille, A., Asada, H.: Describing surfaces. Comput. Vision, Graphics, Image Processing 32, 1–28 (1985)

    Article  MATH  Google Scholar 

  20. Calladine, C.R.: Gaussian curvature and shell structures. The Mathematics of Surfaces, pp. 179–196. Oxford University Press, Oxford (1985)

    Google Scholar 

  21. Chen, H.H., Huang, T.S.: Maximal matching of two three-dimensional point sets. In: Proc. ICPR (October 1986)

    Google Scholar 

  22. Coleman, R., Burr, M., Souvaine, D., Cheng, A.: An intuitive approach to measuring protein surface curvature. Proteins: structure, function and bioinformatics 61(4), 1068–1074

    Google Scholar 

  23. Fan, T.G., Medioni, G., Nevatia, R.: Description of surfaces from range data using curvature properties. In: Proc. CVPR (May 1986)

    Google Scholar 

  24. Forsyth, D.A., Fleck, M.M.: Automatic detection of human nudes. International Journal of Computer Vision 32(1), 63–77 (1999)

    Article  Google Scholar 

  25. Forsyth, D.A., Fleck, M.M.: Body Plans. In: Proc. CVPR 1997, pp. 678–683 (1997)

    Google Scholar 

  26. Forsyth, D.A., Fleck, M.M.: Identifying nude pictures. In: Proceeding of Third IEEE Workshop on Applications of Computer Vision, pp. 103–108 (1996)

    Google Scholar 

  27. Goldgof, D.B., Huang, T.S., Lee, H.: Curvature based approach to terrain recognition. Coord. Sci. Lab., Univ. Illinois, Urbana-Champaign, Tech. Note ISP-910 (April 1989)

    Google Scholar 

  28. Goldgof, D.B., Huang, T.S., Lee, H.: Feature extraction and terrain matching. In: Proc. IEEE Comput. Soc. Conf. Comput. Vision Pattern Recognition, Ann Arbor, MI (May 1988)

    Google Scholar 

  29. Goldgof, D.B., Huang, T.S., Lee, H.: A Curvature-Based Approach to Terrain Recognition  11(11), 1213–1217 (1989)

    Google Scholar 

  30. Gordon, G.: Face recognition based on depth and curvature features. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Champaign, Illinois, pp. 108–110 (1992)

    Google Scholar 

  31. Haralick, R.M., Sternberg, S.R., Zhuang, X.: Image analysis using mathematical morphology. IEEE Trans. Pattern Anal. Machine Intell. PAMI 9(4), 532–550 (1987)

    Article  Google Scholar 

  32. http://www.dace.co.uk/proportion.htm

  33. Jones, P.R.M., Rioux, M.: Three-dimensional surface anthropometry: applications to the human body. Optics and Lasers in Engineering 28, 89–117 (1997)

    Article  Google Scholar 

  34. Li, P., Corner, B.D., Paquette, S.: Evaluation of a surface curvature based landmark extraction method for three dimensional head scans. In: International Ergonomics Conference, Seoul (2003)

    Google Scholar 

  35. Liu, X., Kim, W., Drerup, B.: 3D Characterization and Localization of Anatomical Landmarks of the Foot. In: Proceeding (417), Biomedical Engineering. Acta Press (2004), http://www.actapress.com/PaperInfo.aspx?PaperID=16382

  36. Fleck, M.M., Forsyth, D.A., Bregler, C.: Finding naked people. In: Buxton, B.F., Cipolla, R. (eds.) ECCV 1996. LNCS, vol. 1065, pp. 593–602. Springer, Heidelberg (1996)

    Chapter  Google Scholar 

  37. Ratner, P.: 3-D human modeling and animation. John Wiley & Sons, Chichester (2003)

    Google Scholar 

  38. Robinette, K.M., Blackwell, S., Daanen, H.A.M., Fleming, S., Boehmer, M., Brill, T., Hoeferlin, D., Burnsides, D.: Civilian American and European Surface Anthropometry Resource (2002)

    Google Scholar 

  39. Ioffe, S., Forsyth, D.A.: Probabilistic methods for finding people. International Journal of Computer Vision 43(1), 45–68 (2001)

    Article  MATH  Google Scholar 

  40. Sonka, M., et al.: Image processing, analysis and machine vision. PWS Publishing (1999)

    Google Scholar 

  41. Suikerbuik, C.A.M.: Automatic Feature Detection in 3D Human Body Scans. Master thesis INF/SCR-02-23, Institute of Information and Computer Sciences. Utrecht University (2002)

    Google Scholar 

  42. Suikerbuik, R., Tangelder, H., Daanen, H., Oudenhuijzen, A.: Automatic feature detection in 3D human body scans. In: Proceedings of SAE Digital Human Modeling Conference, 04-DHM-52 (2004)

    Google Scholar 

  43. Mathworks MRI Phantom, http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=1759&objectType=file

  44. NLM, Visible Human Project, http://www.nlm.nih.gov/research/visible/visible_human.html

  45. DARPA Virtual Soldier, http://www.wired.com/news/medtech/0,1286,60016,00.html

  46. Post-Gazette News about Digital Museum Project, http://www.post-gazette.com/pg/04348/425914.stm

  47. Virtual Colonoscopy, http://www.cs.sunysb.edu/~vislab/sample_images/colonoscopy/

  48. Neill, D.B., Moore, A.W.: Anomalous spatial cluster detection. In: Proc. KDD 2005 Workshop on Data Mining Methods for Anomaly Detection, pp. 41–44 (2005)

    Google Scholar 

  49. Neill, D.B., Moore, A.W.: Rapid detection of significant spatial clusters. In: Proc. 10th ACM SIGKDD Conf. on Knowledge Discovery and Data Mining, pp. 256–265 (2004)

    Google Scholar 

  50. Salvador, S., Chan, P.: Fastdtw: Toward accurate dynamic time warping in linear time and space. In: KDD Workshop on Mining Temporal and Sequential Data (2004)

    Google Scholar 

  51. Shyu, M.-L., Chen, S.-C., Sarinnapakorn, K., Chang, L.-W.: A novel anomaly detection scheme based on principal component classifier. In: Proceedings of the IEEE Foundations and New Directions of Data Mining Workshop (2003)

    Google Scholar 

  52. Zhang, J., Zulkernine, M.: Anomaly Based Network Intrusion Detection with Unsupervised Outlier Detection. In: Symposium on Network Security and Information Assurance – Proc. of the IEEE International Conference on Communications (ICC), Istanbul, Turkey (June 2006)

    Google Scholar 

  53. Burbeck, K., Nadjm-Tehrani, S.: ADWICE: Anomaly Detection with Real-time Incremental Clustering. In: Park, C.-s., Chee, S. (eds.) ICISC 2004. LNCS, vol. 3506. Springer, Heidelberg (2005)

    Google Scholar 

  54. Gonzalez, D.D.: An Immuno-Fuzzy Approach to Anomaly Detection. In: The proceedings of the 12th IEEE International Conference on Fuzzy Systems (FUZZIEEE), May 25-28, vol. 2, pp. 1219–1224 (2003)

    Google Scholar 

  55. Wise, J.A., Thomas, J.J., Pennock, K., Lantrip, D., Pottier, M., Schur, A., Crow, V.: Visualizing the non-visual: spatial analysis and interaction with information from text documents. In: Proceedings of the 1995 IEEE Symposium on Information Visualization, Atlanta, Georgia, October 30-31, p. 51 (1995)

    Google Scholar 

  56. Rosenfeld, R.: Digital straight line segments. IEEE Trans. On Computers 23, 1264–1269 (1974)

    Article  MathSciNet  MATH  Google Scholar 

  57. Oppenheim, A.V., et al.: Signals and Systems. Prentice-Hall, Englewood Cliffs (1983)

    MATH  Google Scholar 

  58. Keller, P., McMkin, L., Sheen, D., McKinnon, A., Summet, A.J.: Privacy Algorithm for Cylindrical Holographic Weapons Surveillance Systems. In: Lee, J., Shim, J., Lee, S.-g., Bussler, C.J., Shim, S. (eds.) DEECS 2006. LNCS, vol. 4055, pp. 476–483. Springer, Heidelberg (2006)

    Google Scholar 

  59. Sheen, D.M., et al.: Concealed explosive detection on personnel using a wideband holographic millimeter-wave imaging system. In: AEROSENSE Conference, Proceedings of the SPIE, Orlando, FL, vol. 2755 (1996)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    Yang Cai, Iryna Pavlyshak, Joseph Laws & James Hoburg

  2. Ansoft, Inc., Pittsburgh, PA, USA

    Ryan Magargle

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  1. Yang Cai
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Editors and Affiliations

  1. Ambient Intelligence Lab, CIC-2218, Carnegie Mellon University, 4720 Forbes Avenue, PA 15213, Pittsburgh, USA

    Yang Cai

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Cai, Y., Pavlyshak, I., Laws, J., Magargle, R., Hoburg, J. (2008). Augmented Privacy with Virtual Humans. In: Cai, Y. (eds) Digital Human Modeling. Lecture Notes in Computer Science(), vol 4650. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89430-8_10

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  • DOI: https://doi.org/10.1007/978-3-540-89430-8_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89429-2

  • Online ISBN: 978-3-540-89430-8

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