ROTATIONAL INVARIANCE AT FIXATION POINTS - Experiments using Human Gaze Data

Johannes Steffen, Christian Hentschel, Afra'a Ahmad Alyosef, Klaus Toennies, Andreas Nuernberger

2012

Abstract

An important aspect in machine vision concerns the extraction of meaningful patterns at salient image regions. Invariance w.r.t. affine transformations has usually been claimed to be a crucial attribute of these regions. While continuing research on the human visual cortex has suggested the correctness of these assumptions at least in later stages of vision, only lately the availability of accurate and cheap eye tracking devices has offered the possibility to provide empirical evidence to these claims. We present an experimental setting that is qualified to analyse various assumptions on human gaze target properties. The proposed setting aims at reducing high-level influence on the fixation process as much as possible. As a proof of concept we present results for the assumption human fixation targeting is rotational invariant. Even though high-level aspects could not be completely suppressed, we were able to detect and analyse this relation in the gaze data. It was found that there is a significant correlation between fixated regions within stimuli over different orientations.

References

  1. Alyosef, A. A. (2011). Comparison of interest points of computer vision detectors with human fixation data. Master's thesis, University of Magdeburg, Germany.
  2. Bergen, J. R. and Julesz, B. (1983). Parallel versus serial processing in rapid pattern discrimination. Nature, 303:696-698.
  3. Biederman, I. (1987). Recognition-by-components: A theory of human image understanding. Psychological Review, 94(2):115-147.
  4. Corbetta, M., Kincade, J. M., Ollinger, J. M., McAvoy, M. P., and Shulman, G. L. (2000). Voluntary orienting is dissociated from target detection in human posterior parietal cortex. Nature neuroscience, 3(3):292-7.
  5. Deco, G. and Rolls, E. T. (2004). A neurodynamical cortical model of visual attention and invariant object recognition. Vision research, 44(6):621-42.
  6. Dobbins, A., Zucker, S. W., and Cynader, M. S. (1989). Endstopping and curvature. Vision Research, 29(10):1371-1387.
  7. Engelke, U., Liu, H., Zepernick, H.-J., Heynderickx, I., and Maeder, A. (2010). Comparing two eye-tracking databases: The effect of experimental setup and image presentation time on the creation of saliency maps. International Picture Coding Symposium.
  8. Farivar, R. (2009). recognition. 153.
  9. Dorsalventral integration in object Brain Research Reviews, 61(2):144 -
  10. Harding, P. and Robertson, N. (2009). A comparison of feature detectors with passive and task-based visual saliency. LNCS, 5575:716-725.
  11. Heitger, F., Rosenthaler, L., von der Heydt, R., Peterhans, E., and Kübler, O. (1992). Simulation of neural contour mechanisms: from simple to end-stopped cells. Vision Research, 32(5):963-981.
  12. Henderson, J. M. (2003). Human gaze control during realworld scene perception. Trends in Cognitive Neuroscience, 7(11):498-504.
  13. Hopfinger, J. B., Buonocore, M. H., and Mangun, G. R. (2000). The neural mechanisms of top-down attentional control. Nature neuroscience, 3(3):284-91.
  14. Hubel, D. and Wiesel, T. (1965). Receptive fields and functional architecture in two nonstriate visual areas (18 and 19) of the cat. Journal of Neurophysiology, 28.
  15. Itti, L., Koch, C., and Niebur, E. (1998). A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(11):1254-1259.
  16. Koch, C. and Ullman, S. (1985). Shifts in selective visual attention: towards the underlying neural circuitry. Human Neurobiology, 4(4):219-227.
  17. Krieger, G., Rentschler, I., Hauske, G., Schill, K., and Zetzsche, C. (2000). Object and scene analysis by saccadic eye-movements: an investigation with higherorder statistics. Spatial vision, 13(2-3):201-14.
  18. Mannan, S., Ruddock, K., and Wooding, D. (1996). The relationship between the locations of spatial features and those of fixations made during visual examination of briefly presented images. Spatial Vision, 10(3):165-188.
  19. Marr, D. and Hildreth, E. (1980). Theory of Edge Detection. Proceedings of the Royal Society B: Biological Sciences, 207(1167):187-217.
  20. Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., and Gool, L. V. (2005). A comparison of affine region detectors. International Journal of Computer Vision, 65:43-72.
  21. Niebur, E. and Koch, C. Control of selective visual attention: modeling the” where” pathway. Advances in neural information processing systems, pages 802- 808.
  22. Parkhurst, D., Law, K., and Niebur, E. (2002). Modeling the role of salience in the allocation of overt visual attention. Vision research, 42(1):107-23.
  23. Parkhurst, D. J. and Niebur, E. (2003). Scene content selected by active vision. Spatial vision, 16(2):125-54.
  24. Pasupathy, a. and Connor, C. E. (1999). Responses to contour features in macaque area V4. Journal of neurophysiology, 82(5):2490-502.
  25. Rajashekar, U., van der Linde, I., Bovik, A. C., and Cormack, L. K. (2007). Foveated analysis of image features at fixations. Vision Research, 47:3160-3172.
  26. Rodrigues, J. and du Buf, J. (2006). Multi-scale keypoints in v1 and beyond: object segregation, scale selection, saliency maps and face detection. BioSystems, 86.
  27. Treisman, A. M. and Gelade, G. (1980). A featureintegration theory of attention. Cognitive psychology, 12(1):97-136.
  28. Tuytelaars, T. and Mikolajczyk, K. (2007). Local invariant feature detectors: A survey. Foundations and Trends in Computer Graphics and Vision, 3(3):177-280.
  29. Vosskuehler, A. (2009). Ogama description (version 2.5).
  30. Wallis, G., Rolls, E., and Foldiak, P. (1993). Learning invariant responses to the natural transformations of objects. Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan), 2:1087-1090.
Download


Paper Citation


in Harvard Style

Steffen J., Hentschel C., Ahmad Alyosef A., Toennies K. and Nuernberger A. (2012). ROTATIONAL INVARIANCE AT FIXATION POINTS - Experiments using Human Gaze Data . In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM, ISBN 978-989-8425-99-7, pages 451-456. DOI: 10.5220/0003782104510456


in Bibtex Style

@conference{icpram12,
author={Johannes Steffen and Christian Hentschel and Afra'a Ahmad Alyosef and Klaus Toennies and Andreas Nuernberger},
title={ROTATIONAL INVARIANCE AT FIXATION POINTS - Experiments using Human Gaze Data},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,},
year={2012},
pages={451-456},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003782104510456},
isbn={978-989-8425-99-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,
TI - ROTATIONAL INVARIANCE AT FIXATION POINTS - Experiments using Human Gaze Data
SN - 978-989-8425-99-7
AU - Steffen J.
AU - Hentschel C.
AU - Ahmad Alyosef A.
AU - Toennies K.
AU - Nuernberger A.
PY - 2012
SP - 451
EP - 456
DO - 10.5220/0003782104510456