204
N. Blanik
11. Blanik N (2010) Konzept und Realisierung eines kontaktlosen Messsystems für die
ortsaufgelöste Erfassung der Sauerstoffsättigung der Haut. Diploma thesis, RWTH Aachen
University
12. F. Wieringa, F. Mastik, A.F.W. van der Steen, Contactless multiple wavelength photoplethysmographic imaging: a first step toward spo2 camera technology. Ann. Biomed. Eng. 33(8),
1034–1041 (2005)
13. G. Isenberg, Design and evaluation of a robust illumination system for camera-based, noncontact detection of vital parameters in neonatology. Master thesis, RWTH Aachen University
(2015)
14. M. Hülsbusch, V. Blazek, Rhytmical phenomena in dermal perfusion—proved assessment
strategies and new discoveries, in Proceedings of International Conference Trend in Biomedical
Engineering, Zilina, Slovakia, (2005) pp. 58–63
15. N. Blanik, A.B. Abbas, B. Venema, V. Blazek, S. Leonhardt, Hybrid optical imaging technology
for long-term remote monitoring of skin perfusion and temperature behavior. JBO 19(1). https://
doi.org/10.1117/1.JBO.19.1.016012
16. M. Hülsbusch, V. Blazek, Photoplethysmography Imaging (PPGI): advanced strategies for the
2d visualisation of skin perfusion, in Computer Aided Noninvasive Vascular Diagnostics, ed.
by U. Schultz-Ehrenburg, V. Blazek, Mainz Verlag, Aachen, ISBN 3-89653-882-9 (2003),
pp. 69–74
17. D. Forsyth, J. Ponce, Computer Vision: A Modern Approach, 2nd edn. (Pearson, Boston, 2012).
ISBN 0273764144
18. M. Paul, N. Blanik, V. Blazek, S. Leonhardt, An efficient method for facial component detection
in thermal images, in 12th International Conference on Quality Control by Artificial Vision,
Proceedings of SPIE, vol. 9534, 95340P (2015). https://doi.org/10.1117/12.2182760
19. B. Jähne, Digital Image Processing (Springer Science & Business Media, 2005)
20. M.-H. Yang, N. Ahuja Face detection and gesture recognition for human-computer interaction
(Springer Science+Buisiness Media, 2001)
21. F. Massanes, M. Cadennes, J.G. Brankov, Compute-unified device architecture implementation
of a block-matching algorithm for multiple graphical processing unit cards. J. Electron Imag.
20(3), 033004 (2011). https://doi.org/10.1117/1.3606588
22. A. Gyaourova, C. Kamath, S.-C. Cheung, Block matching for object tracking. LLNL Technical
report, UCRL-TR-200271 (2003)
23. C. Mayntz, J.M. Frahm, T. Aach, G. Schmitz, Beschleunigung und Bewertung blockbasierter
Bewegungsschätzmethoden für die Röntgenfluoroskopie (Mustererkennung. Springer, Berlin
Heidelberg, In Sommer G, Krüger N, Perwass C, 2000) https://doi.org/10.1007/978-3-64259802-9_16, ISBN 978-3-540-67886-1, pp. 123–130
24. G.A. Jones, Constraint, optimization, and hierarchy: reviewing stereoscopic correspondence
of complex features. Comput. Vision Image Understand. 65(1), pp. 57–78 (1997). https://doi.
org/10.1006/cviu.1996.0482
25. B. Heisele, Objektdetektion in Straßenverkehrsszenen durch Auswertung von Farbbildfolgen.
PhD thesis, Universität Stuttgart, VDI-Verlag, Düsseldorf (1998)
26. S.-G. Wie, L. Yang, Z. Chen, Z.-F. Liu, Motion detection based on optical flow and self-adaptive
threshold segmentation, in Proc. Eng.15, 3471–3476, CEIS (2011). https://doi.org/10.1016/j.
proeng.2011.08.650
27. B.K.P. Horn, B.G. Schunck, Determining optical flow. Artif. Intell. 17(1–3), 185–203. https://
doi.org/10.1016/0004-3702(81)90024-2
28. B.D. Lucas, T. Kanade T, An iterative image registration technique with an application to stereo
vision, in Proceedings of Imaging Understanding Workshop (1981), pp. 121–130
29. C. Tomasi, T. Kanade, Detection and tracking of point features. Carnegie Mellon University,
Technical Report CMU-CS-91–132 (1991)
30. P. Viola, M. Jones, Robust real-time object detection. Int. J. Comput. Vision 4, 51–52 (2001)
31. D. G. Lowe, Method and apparatus for identifying scale invariant features in an image and use
of same for locating an object in an image, U.S. patent 6,711,293 B1 (1999)
N. Blanik
11. Blanik N (2010) Konzept und Realisierung eines kontaktlosen Messsystems für die
ortsaufgelöste Erfassung der Sauerstoffsättigung der Haut. Diploma thesis, RWTH Aachen
University
12. F. Wieringa, F. Mastik, A.F.W. van der Steen, Contactless multiple wavelength photoplethysmographic imaging: a first step toward spo2 camera technology. Ann. Biomed. Eng. 33(8),
1034–1041 (2005)
13. G. Isenberg, Design and evaluation of a robust illumination system for camera-based, noncontact detection of vital parameters in neonatology. Master thesis, RWTH Aachen University
(2015)
14. M. Hülsbusch, V. Blazek, Rhytmical phenomena in dermal perfusion—proved assessment
strategies and new discoveries, in Proceedings of International Conference Trend in Biomedical
Engineering, Zilina, Slovakia, (2005) pp. 58–63
15. N. Blanik, A.B. Abbas, B. Venema, V. Blazek, S. Leonhardt, Hybrid optical imaging technology
for long-term remote monitoring of skin perfusion and temperature behavior. JBO 19(1). https://
doi.org/10.1117/1.JBO.19.1.016012
16. M. Hülsbusch, V. Blazek, Photoplethysmography Imaging (PPGI): advanced strategies for the
2d visualisation of skin perfusion, in Computer Aided Noninvasive Vascular Diagnostics, ed.
by U. Schultz-Ehrenburg, V. Blazek, Mainz Verlag, Aachen, ISBN 3-89653-882-9 (2003),
pp. 69–74
17. D. Forsyth, J. Ponce, Computer Vision: A Modern Approach, 2nd edn. (Pearson, Boston, 2012).
ISBN 0273764144
18. M. Paul, N. Blanik, V. Blazek, S. Leonhardt, An efficient method for facial component detection
in thermal images, in 12th International Conference on Quality Control by Artificial Vision,
Proceedings of SPIE, vol. 9534, 95340P (2015). https://doi.org/10.1117/12.2182760
19. B. Jähne, Digital Image Processing (Springer Science & Business Media, 2005)
20. M.-H. Yang, N. Ahuja Face detection and gesture recognition for human-computer interaction
(Springer Science+Buisiness Media, 2001)
21. F. Massanes, M. Cadennes, J.G. Brankov, Compute-unified device architecture implementation
of a block-matching algorithm for multiple graphical processing unit cards. J. Electron Imag.
20(3), 033004 (2011). https://doi.org/10.1117/1.3606588
22. A. Gyaourova, C. Kamath, S.-C. Cheung, Block matching for object tracking. LLNL Technical
report, UCRL-TR-200271 (2003)
23. C. Mayntz, J.M. Frahm, T. Aach, G. Schmitz, Beschleunigung und Bewertung blockbasierter
Bewegungsschätzmethoden für die Röntgenfluoroskopie (Mustererkennung. Springer, Berlin
Heidelberg, In Sommer G, Krüger N, Perwass C, 2000) https://doi.org/10.1007/978-3-64259802-9_16, ISBN 978-3-540-67886-1, pp. 123–130
24. G.A. Jones, Constraint, optimization, and hierarchy: reviewing stereoscopic correspondence
of complex features. Comput. Vision Image Understand. 65(1), pp. 57–78 (1997). https://doi.
org/10.1006/cviu.1996.0482
25. B. Heisele, Objektdetektion in Straßenverkehrsszenen durch Auswertung von Farbbildfolgen.
PhD thesis, Universität Stuttgart, VDI-Verlag, Düsseldorf (1998)
26. S.-G. Wie, L. Yang, Z. Chen, Z.-F. Liu, Motion detection based on optical flow and self-adaptive
threshold segmentation, in Proc. Eng.15, 3471–3476, CEIS (2011). https://doi.org/10.1016/j.
proeng.2011.08.650
27. B.K.P. Horn, B.G. Schunck, Determining optical flow. Artif. Intell. 17(1–3), 185–203. https://
doi.org/10.1016/0004-3702(81)90024-2
28. B.D. Lucas, T. Kanade T, An iterative image registration technique with an application to stereo
vision, in Proceedings of Imaging Understanding Workshop (1981), pp. 121–130
29. C. Tomasi, T. Kanade, Detection and tracking of point features. Carnegie Mellon University,
Technical Report CMU-CS-91–132 (1991)
30. P. Viola, M. Jones, Robust real-time object detection. Int. J. Comput. Vision 4, 51–52 (2001)
31. D. G. Lowe, Method and apparatus for identifying scale invariant features in an image and use
of same for locating an object in an image, U.S. patent 6,711,293 B1 (1999)