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Center for Unified Biometrics and Sensors: Projects, Technologies, Unique Capabilities

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  • Some more detail concerning the impact of ruled line removal on word recognition:We extracted all the test word images from lined pages and measured the top choice recognition performance. Here are the numbers: -- Total word images in test set : 848 from a total of 274 pages. Of these: -- Number of word images from pages with ruled lines: 460, from 146 lined pages. -- The ratio of words and pages with ruled lines in the 34 PAW data set: 460/848 = 54.25% (word), 146/274=53.28% (pages).Recognition performance on words from lined pages: -- Top1: Earlier: 318/460 = 69.13% Now: 349/460 = 75.87% The ruled line removal improves the word recognition for top 1 by 6.74% (evaluated on words from lined pages). Overall improvement for top 1 is by 4.13% (evaluated using test set including all word images from lined or non-lined pages - which we had reported earlier).Also the PAW recognizer is a straightforward implementation using a k-nearest neighbor classifier. The features used are CUBS Gradient, Structure and ConcavityFeatures. The classifier is a very simple implementation that can be improved and its purpose was for testing the effectiveness of our features.
  • CUBS expertise

    1. 1. CUBS<br />R&D Portfolio<br />VenuGovindaraju<br />Distinguished Professor, SUNY Buffalo<br />
    2. 2. Overview<br />Unique Capabilities<br />Sponsors<br />Technology Transfer Record<br />Projects<br />Biometrics<br />Document Recognition and Retrieval<br />Security<br />People<br />
    3. 3. Unique Capabilities<br />Faculty strengths in multiple disciplines<br />Behavioral Sciences, Social Issues<br />Computer Vision, Visualization<br />Chemical and Biological Sensors<br />Pattern Recognition, Machine Learning<br />Smart Environments, Pervasive Computing<br />Spectroscopy<br />Solid record of transferring of technology to field <br />Large pool of current PhD students (10)<br />Growing pool of PhD alumni in industry (25)<br />Several current projects with industry<br />
    4. 4. Sponsors(last 5 years)<br />ACIS, Buffalo, NY<br />Applied Media Analysis, College Park, MD<br />BBN Technologies, Cambridge, MA<br />Buffalo Computer Graphics, Blasdell, NY<br />CUBRC, Cheektowaga, NY<br />Fujitsu, Sunnyvale, CA<br />HP Labs, India<br />Health Transaction Network, Williamsville, NY<br />Matrix, Niagara Falls, NY<br />Ultra-Scan, Amherst, NY<br /><ul><li>Army Research Labs
    5. 5. Defense Intelligence Agency (DIA)
    6. 6. Directorate of Central Intelligence (DCI)
    7. 7. National Endowment of Humanities (NEH)
    8. 8. National Science Foundation (NSF)
    9. 9. NYSTAR
    10. 10. Oishei Foundation</li></li></ul><li>Technology Transfer<br />4 US patents awarded<br />Biometric convolution; Handwriting comparisons; Diagnosis of physiological states; Handwriting recognition<br />4 US patents pending<br />Fingerprint hashing; Deceit and verity; Document classification; Document Image<br />capture <br />Licensed technology to industry<br />Kyos Systems, Xact Data, Buffalo Computer Graphics, Lockheed Martin<br />USPS 1999 Annual Report<br />"USPS issued a contract to SUNY Buffalo to develop the handwriting recognition technology. ….. an estimated 400 million pieces of mail were automatically routed ….. saved the Postal Service at least $90 million in its first year in the field.<br />
    11. 11. BIOMETRICS<br />CUBS<br />
    12. 12. Anthropometrics<br />SKIN TONE<br />
    13. 13. Fingerprint Indexing<br />Enrollment Phase<br />Searching Phase<br />
    14. 14. CryptographyCancelable Biometrics<br />
    15. 15. SensorsSkin spectroscopy and “liveness”<br />
    16. 16. Fusion<br />
    17. 17. Spoofing in Multimodal Systems<br />
    18. 18. Facial Passwords<br />
    19. 19. Q: The suspect is male<br />1st Iteration<br />Pruned Set<br />Q: The suspect has a beard<br />2nd Iteration<br />Pruned Set<br />Q: The suspect wears spectacles<br />3rd Iteration<br />SUSPECT<br />Soft BiometricsSemantic Face Retrieval<br />Original Set<br />
    20. 20. Unobtrusive People Tracking<br />Freedom from Continuous Surveillance<br />RECOGNIZE<br />REASON<br />Evolutionary<br />Recognition<br />RETRIEVE<br />Did Bob and Frank meet at the library yesterday?<br />Given building map, occupants, schedules, sensor locations<br />
    21. 21. Soft Biometrics<br />Crash scene analysis<br />
    23. 23. Document Enhancement,<br />
    24. 24. Multilingual Information Retrieval<br />Q: Can we have a searchable archive of world’s newspapers?<br />Q: All newspapers in any language translated to a common language?<br />Central Repository<br />Searchable database<br />(digitized)<br />
    25. 25. Smart EMR<br />
    26. 26. Handwriting Forensics<br />
    27. 27. ?<br />?<br />?<br />Web SecurityVerify humanness<br />MACHINES FAIL<br />Synthetic handwriting generator poses questions in varying writing styles<br />English!<br />HUMANS SUCCEED<br />
    28. 28. security<br />CUBS<br />
    29. 29. Soft BiometricsExpressions<br />+<br />=<br />AU 6<br />AU 12<br />AU 6 & 12<br />+<br />+<br />=<br />AU 1<br />AU 2<br />AU 4<br />AU 1, 2 & 4<br />+<br />+<br />=<br />AU 1<br />AU 4<br />AU 15<br />AU 1, 4 & 15<br />FACS<br />FEAR<br />HAPPY<br />ANGER<br />SAD<br />FEAR<br />HAPPY<br />SAD<br />Facial Expression Manifold<br />
    30. 30. Gaze Tracking<br />
    31. 31. Soft BiometricsEmotional States<br />
    32. 32. Deceit and Verity<br />
    33. 33. PEOPLE<br />CUBS<br />
    34. 34. PeopleFaculty<br />Frank Bright<br />SUNY Distinguished Professor<br />Biological, Chemical Sensors<br />VenuGovindaraju<br />SUNY Distinguished Professor<br />Machine Learning<br />Director<br />Mark Frank<br />Professor<br />Behavioral Sciences<br />Raymond Fu<br />Assistant Professor<br />Computer Vision, Visualization<br />Alex Cartwright<br />Professor<br />Spectroscopy, Photonics<br />Bharat Jayaraman<br />Professor<br />Cyber Physical Systems<br />
    35. 35. PeopleStaff<br /><ul><li>Philip Kilinskas</li></ul>Software Engineer<br /> Systems <br /><ul><li>RangaSetlur</li></ul> Principal Research Scientist<br /> Pattern Recognition Systems<br /><ul><li>Sergey Tulyakov</li></ul>Research Scientist<br /> Biometrics Fusion<br />AmalHarb<br />Communications Specialist<br /> Informatics, Psychology<br />IfeomaNwogu<br />Research Scientist<br /> Computer Vision, Ontology<br />Zhixin Shi<br />Senior Research Scientist<br />Mathematics<br />
    36. 36. PeopleCurrent PhD students; Research topics <br />Xi Cheng Biometric Fusion<br />Gaurav Kumar Mobile Device Apps<br />UtkarshPoruwal People Tracking<br />ChetanRamaiah Writer Identification<br />Manavender Reddy Gesture Recognition<br />Ricardo N. Rodriguez Multimodal Fusion<br />ArtiShivaram Mobile Device Apps<br />SafwanWshah Arabic Handwriting Recognition<br />Daekeun You Medical Analytics<br />Yingbou Zhou Image Segmentation<br />
    37. 37. Ph.D. Alumni (22)<br />
    38. 38. References<br />
    39. 39. Contact <br />VenuGovindaraju<br /><br />University at Buffalo<br />State University of New York<br />