A two-level real-time vision machine combining coarse- and fine-grained parallelism

Journal of Real-Time Image Processing

Volumn 5, Issue 4, 2010, Pages 291-304

  Jensen, Lars Baunegaard With ^a   Kjær Nielsen, Anders ^a   Pauwels, Karl ^b   Jessen, Jeppe Barsøe ^a   van Hulle, Marc ^b   Krüger, Norbert ^a  

^a UNIVERSITY OF SOUTHERN DENMARK   (Denmark)

^b KU LEUVEN UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

Early vision; GPU computing; Hybrid parallelism; Mid level vision; Multi core

Indexed keywords

EARLY VISION; GPU COMPUTING; HYBRID PARALLELISM; MID-LEVEL VISION; MULTI CORE;

AUTOMOBILE DRIVERS; OPTICAL FLOWS; STEREO VISION;

COMPUTER VISION;

EID: 78649324043     PISSN: 18618200     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11554-010-0159-4     Document Type: Article

References (50)

1. Aarno, D., Sommerfeld, J., Kragic, D., Pugeault, N., Kalkan, S., Wörgötter, F., Kraft, D., Krüger, N.: Early reactive grasping with second order 3d feature relations. In: The IEEE International Conference on Advanced Robotics, Jeju Island, Korea (2007).
2. Adelson, E. H., Anderson, C. H., Bergen, J. R., Burt, P. J., Ogden, J. M.: Pyramid methods in image processing. RCA Eng. 29(6), 33-41 (1984).
3. Aloimonos, Y., Shulman, D.: Integration of Visual Modules-An Extension of the Marr Paradigm. Academic Press, London (1989).
4. Amdahl, G. M.: Validity of the single processor approach to achieving large scale computing capabilities, pp. 79-81 (2000).
5. Baseski, E., Kraft, D., Krüger, N.: Road interpretation for driver assistance based on an early cognitive vision system. VISAPP (2009).
6. Baker, Z. K., Gokhale, M. B., Tripp, J. L.: Matched filter computation on FPGA, cell and GPU. Field-Programmable Custom Computing Machines. Annual IEEE Symposium, pp. 207-218 (2007). doi: 10. 1109/FCCM. 2007. 52.
7. Bouguet, J. Y.: Camera Calibration Toolbox for Matlab (2008). http://www.vision.caltech.edu/bouguetj/calib_doc/.
8. Bugge. H.: An evaluation of Intel's core i7 architecture using a comparative approach. Comput. Sci. Res. Dev. 23(3-4), 203-209 (2009).
9. Che, S., Li, J., Sheaffer, J., Skadron, K., Lach, J.: Accelerating compute-Intensive applications with GPUs and FPGAs. In: Application Specific Processors, 2008. SASP 2008. Symposium, pp 101-107(2008). doi: 10. 1109/SASP. 2008. 4570793.
10. Daugman, J.: Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by 2D visual cortical filters. J. Opt. Soc. Am. 2(7), 1160-1169 (1985).
11. Detry, R., Pugeault, N., Piater, J.: A probabilistic framework for 3D visual object representation. IEEE Trans. Pattern Anal. Mach. Intell. 31(10), 1790-1803 (2009).
12. ECOVISION: Artificial visual systems based on early-cognitive cortical processing (EU-Project) (2001-2003). http://www. pspcdibeunigeit/ecovision/projecthtml.
13. Felsberg, M., Sommer, G.: The monogenic signal. IEEE Trans. Signal Process. 49(12), 3136-3144 (2001).
14. Felsberg, M., Kalkan, S., Krüger, N.: Continuous dimensionality characterization of image structures. Image Vis. Comput. 27, 628-636 (2009).
15. Fleet, D., Jepson, A.: Computation of component image velocity from local phase information. Int. J. Comput. Vis. 5, 77-104 (1990).
16. Gautama, T., van Hulle, M.: A phase-based approach to the estimation of the optical flow field using spatial filtering. IEEE Trans. Neural Netw. 13(5), 1127-1136 (2002).
17. Granlund, G.: In search of a general picture processing operator. Comput. Graph. Image Process. 8, 155-173 (1978).
18. Granlund, G.: The complexity of vision. Signal Process. 74 (1999).
19. Granlund, G. H., Knutsson, H.: Signal Processing for Computer Vision. Kluwer, Dordrecht (1995).
20. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2000).
21. Hubel, D., Wiesel, T.: Anatomical demonstration of columns in the monkey striate cortex. Nature 221, 747-750 (1969).
22. TM i7 Desktop Processor, Product Brief (2009).
23. Jensen, L. B. W., Kjær-Nielsen, A., Alonso, J. D., Ros, E., Krüger, N.: A hybrid fpga/coarse parallel processing architecture for multi-modal visual feature descriptors. In: RECONFIG '08: Proceedings of the 2008 International Conference on Reconfigurable Computing and FPGAs, pp. 241-246 (2008).
24. Jessen, J. B.: Real time sparse and dense stereo in an early cognitive vision system using cuda. Master's thesis. The Cognitive Vision Group, Maersk Institute, University of Southern Denmark (2009). http://www.mip.sdu.dk/covig/publications/JessenMaster.pdf.
25. Kjær-Nielsen, A., Jensen, L. B. W., Sørensen, A. S., Krüger, N.: A real-time embedded system for stereo vision preprocessing using an fpga. In: RECONFIG '08: Proceedings of the 2008 International Conference on Reconfigurable Computing and FPGAs, pp. 37-42 (2008).
26. Kraft, D., Pugeault, N., Başeski, E., Popovic, M., Kragic, D., Kalkan, S., Wörgötter, F., Krüger, N.: Birth of the Object: Detection of Objectness and Extraction of Object Shape through Object Action Complexes. Special Issue on Cognitive Humanoid Robots of the International Journal of Humanoid Robotics, vol. 5, pp. 247-265 (2009).
27. Krüger, N., Felsberg, M.: An explicit and compact coding of geometric and structural information applied to stereo matching. Pattern Recognit. Lett. 25(8), 849-863 (2004).
28. Krüger, N., Lappe, M., Wörgötter, F.: (2004) Biologically motivated multi-modal processing of visual primitives. The interdisciplinary. J. Artifi. Intell. Simul. Behav. 1(5), 417-428.
29. Lades, M., Vorbrüggen, J., Buhmann, J., Lange, J., von der Malsburg, C., Würtz, R., Konen, W.: Distortion invariant object recognition in the dynamik link architecture. IEEE Trans. Comput. 42(3), 300-311 (1993).
30. Longuet-Higgins, H. C., Prazdny, K.: The interpretation of a moving retinal image. Proc. R. Soc. Lond. Ser. B Biol. Sci. 208, 385-397 (1980).
31. Malvar, H., He L., Cutler, R.: High-quality linear interpolation for demosaicing of Bayer-patterned color images. In: Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP'04). IEEE International Conference on, vol 3, pp iii-485-8 (2004). doi: 10. 1109/ICASSP. 2004. 1326587.
32. Marr, D.: Vision. Freeman, San Francisco (1982).
33. Mosteller, F., Tukey, J.: Data Analysis and Regression: A Second Course in Statistics. Addison-Wesley Reading (1977).
34. Pauwels, K.: Computational modeling of visual attention: neuronal response modulation in the thalamocortical complex and saliency-based detection of independent motion. PhD thesis, K. U. Leuven (2008).
35. Pauwels, K., van Hulle, M.: Realtime phase-based optical flow on the GPU. In: IEEE Conference on Computer Vision and Pattern Recognition, Workshop on Computer Vision on the GPU (2008).
36. Pauwels, K., Krüger, N., Lappe, M., Wörgötter, F., van Hulle, M.: A cortical architecture on parallel hardware for motion processing in real-time. J. Vis. (2010, submitted).
37. Pollen, D., Ronner, S.: Phase-relationships between adjacent simple cells in the visual cortex. Science 212(4501), 1409-1411 (1981).
38. Pugeault, N.: Early Cognitive Vision: Feedback Mechanisms for the Disambiguation of Early Visual Representation. VDM Verlag Dr. Müller, Germany (2008).
39. Pugeault, N., Wörgötter, F., Krüer, N.: Accumulated visual representation for cognitive vision. In Proceedings of the British Machine Vision Conference (BMVC) (2008).
40. Sabatini, S., Gastaldi, G., Solari, F., Diaz, J., Ros, E., Pauwels, K., van Hulle, M., Pugeault, N., Krüger, N.: Compact and accurate early vision processing in the harmonic space. In: International Conference on Computer Vision Theory and Applications, Barcelona, pp. 213-220 (2007).
41. Satish, N., Harris, M., Garland, M.: Designing efficient sorting algorithms for manycore GPUs. In: Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium, pp. 1-10 (2009). doi: 10. 1109/IPDPS. 2009. 5161005.
42. Schiele, B., Crowley, J.: Probabilistic object recognition using multidimensional receptive field histograms. Adv. Neural Info. Process. Syst. 8, 865-871 (1996).
43. Slama, C. C. (ed.): Manual of Photogrammetry. American Society of Photo (1980).
44. Thompson, W., Pong, T.: Detecting moving-objects. Int. J. Comput. Vis. 4, 39-57 (1990).
45. Tröger, P.: The Multi-Core Era-Trends and Challenges. CoRR abs/0810. 5439 (2008).
46. Vernon, D.: The space of cognitive vision. In: Cognitive Vision Systems, Part I: Foundations of Cognitive Vision Systems. LNCS, vol. 3948 (2006).
47. Wilkinson, B.: Computer Architecture (2nd ed.): Design and Performance. Prentice-Hall, Inc., Upper Saddle River (1996).
48. Wörgötter, F., Krüger, N., Pugeault, N., Calow, D., Lappe, M., Pauwels, K., Hulle, M. V., Tan, S., Johnston, A.: Early cognitive vision: Using gestalt-laws for task-dependent, active image-processing. Nat. Comput. 3(3), 293-321 (2004).
49. Zetzsche, C., Krieger, G.: Nonlinear mechanisms and higher-order statistics in biologial vision and electronic image processing: review and perspectives. J. Electron. Imaging 10(1), 56-99 (2001).
50. Zhang, T., Tomasi, C.: On the consistency of instantaneous rigid motion estimation. Int. J. Comput. Vis. 46, 51-79 (2002).