FURTHER STUDIES ON VISUAL PERCEPTION FOR PERCEPTUAL ROBOTICS
Ozer Ciftcioglu, Michael S. Bittermann, I. Sevil Sariyildiz
2007
Abstract
Further studies on computer-based perception by vision modelling are described. The visual perception is mathematically modelled, where the model receives and interprets visual data from the environment. The perception is defined in probabilistic terms so that it is in the same way quantified. At the same time, the measurement of visual perception is made possible in real-time. Quantifying visual perception is essential for information gain calculation. Providing virtual environment with appropriate perception distribution is important for enhanced distance estimation in virtual reality. Computer experiments are carried out by means of a virtual agent in a virtual environment demonstrating the verification of the theoretical considerations being presented, and the far reaching implications of the studies are pointed out.
References
- Adams, B., C. Breazeal, et al., 2000. Humanoid robots: a new kind of tool, Intelligent Systems and Their Applications, IEEE [see also IEEE Intelligent Systems] 15(4): 25-31.
- Ahle, E. and D. Söffker, 2006. A cognitive-oriented architecture to realize autonomous behaviour - part I: Theoretical background. 2006 IEEE Conf. on Systems, Man, and Cybernetics, Taipei, Taiwan.
- Ahle, E. and D. Söffker, 2006. A cognitive-oriented architecture to realize autonomous behaviour - part II: Application to mobile robots. 2006 IEEE Conf. on Systems, Man, and Cybernetics, Taipei, Taiwan.
- Arbib, M. A., 2003. The Handbook of Brain Theory and Neural Networks. Cambridge, MIT Press.
- Beetz, M., T. Arbuckle, et al., 2001. Integrated, planbased control of autonomous robots in human environments, IEEE Intelligent Systems 16(5): 56-65.
- Bigun, J., 2006. Vision with direction, Springer Verlag.
- Bittermann, M. S., I. S. Sariyildiz, et al., 2006. Visual Perception in Design and Robotics, Integrated Computer-Aided Engineering to be published.
- Burghart, C., R. Mikut, et al., 2005. A cognitive architecture for a humanoid robot: A first approach. 2005 5th IEEE-RAS Int. Conf. on Humanoid Robots, Tsukuba, Japan.
- Cataliotti, J. and A. Gilchrist, 1995. Local and global processes in surface lightness perception, Perception & Psychophysics 57(2): 125-135.
- Ciftcioglu, Ö., M. S. Bittermann, et al., 2006. Autonomous robotics by perception. SCIS & ISIS 2006, Joint 3rd Int. Conf. on Soft Computing and Intelligent Systems and 7th Int. Symp. on advanced Intelligent Systems, Tokyo, Japan.
- Ciftcioglu, Ö., M. S. Bittermann, et al., 2006. Studies on visual perception for perceptual robotics. ICINCO 2006 - 3rd Int. Conf. on Informatics in Control, Automation and Robotics, Setubal, Portugal.
- Ciftcioglu, Ö., M. S. Bittermann, et al., 2006. Towards computer-based perception by modeling visual perception: a probabilistic theory. 2006 IEEE Int. Conf. on Systems, Man, and Cybernetics, Taipei, Taiwan.
- Desolneux, A., L. Moisan, et al., 2003. A grouping principle and four applications, IEEE Transactions on Pattern Analysis and Machine Intelligence 25(4): 508- 513.
- Garcia-Martinez, R. and D. Borrajo, 2000. An integrated approach of learning, planning, and execution, Journal of Intelligent and Robotic Systems 29: 47-78.
- Ghosh, K., S. Sarkar, et al., 2006. A possible explanation of the low-level brightness-contrast illusions in the light of an extended classical receptive field model of retinal ganglion cells, Biological Cybernetics 94: 89- 96.
- Hecht-Nielsen, R., 2006. The mechanism of thought. IEEE World Congress on Computational Intelligence WCCI 2006, Int. Joint Conf. on Neural Networks, Vancouver, Canada.
- Hubel, D. H., 1988. Eye, brain, and vision, Scientific American Library.
- Itti, L., C. Koch, et al., 1998. A model of saliency-based visual attention for rapid scene analysis, IEEE Trans. on Pattern Analysis and Machine Intelligence 20(11): 1254-1259.
- Korn, G. A. and T. M. Korn, 1961. Mathematical handbook for scientists and engineers. New York, McGraw-Hill.
- Levine, M. W. and J. M. Sheffner, 1981. Fundamentals of Sensation and Perception. London, Addison-Wesley.
- Marr, D., 1982. Vision, Freeman.
- O'Regan, J. K., H. Deubel, et al., 2000. Picture changes during blinks: looking without seeing and seeing without looking, Visual Cognition 7: 191-211.
- Oriolio, G., G. Ulivi, et al., 1998. Real-time map building and navigation for autonomous robots in unknown environments, IEEE Trans. on Systems, Man and Cybernetics - Part B: Cybernetics 28(3): 316-333.
- Palmer, S. E., 1999. Vision Science. Cambridge, MIT Press.
- Papoulis, A., 1965. Probability, Random Variables and Stochastic Processes. New York, McGraw-Hill.
- Pentland, A., 1987. A new sense of depth, IEEE Trans. on Pattern Analysis and Machine Intelligence 9: 523-531.
- Poggio, T. A., V. Torre, et al., 1985. Computational vision and regularization theory, Nature 317(26): 314-319.
- Posner, M. I. and S. E. Petersen, 1990. The attention system of the human brain, Annual Review of Neuroscience 13: 25-39.
- Prince, S. J. D., A. D. Pointon, et al., 2002. Quantitative analysis of the responses of V1 Neurons to horizontal disparity in dynamic random-dot stereograms, J Neurophysiology 87: 191-208.
- Rensink, R. A., J. K. O'Regan, et al., 1997. To see or not to see: The need for attention to perceive changes in scenes, Psychological Science 8: 368-373.
- Söffker, D., 2001. From human-machine-interaction modeling to new concepts constructing autonomous systems: A phenomenological engineering-oriented approach., Journal of Intelligent and Robotic Systems 32: 191-205.
- Taylor, J. G., 2006. Towards an autonomous computationally intelligent system (Tutorial). IEEE World Congress on Computational Intelligence WCCI 2006, Vancouver, Canada.
- Treisman, A. M., 2006. How the deployment of attention determines what we see, Visual Cognition 14(4): 411- 443.
- Treisman, A. M. and G. Gelade, 1980. A featureintegration theory of attention, Cognitive Psychology 12: 97-136.
- Wang, M. and J. N. K. Liu, 2004. Online path searching for autonomous robot navigation. IEEE Conf. on Robotics, Automation and Mechatronics, Singapore.
- Wiesel, T. N., 1982. Postnatal development of the visual cortex and the influence of environment (Nobel Lecture), Nature 299: 583-591.
Paper Citation
in Harvard Style
Ciftcioglu O., S. Bittermann M. and Sevil Sariyildiz I. (2007). FURTHER STUDIES ON VISUAL PERCEPTION FOR PERCEPTUAL ROBOTICS . In Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO, ISBN 978-972-8865-83-2, pages 468-477. DOI: 10.5220/0001642504680477
in Bibtex Style
@conference{icinco07,
author={Ozer Ciftcioglu and Michael S. Bittermann and I. Sevil Sariyildiz},
title={FURTHER STUDIES ON VISUAL PERCEPTION FOR PERCEPTUAL ROBOTICS},
booktitle={Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,},
year={2007},
pages={468-477},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001642504680477},
isbn={978-972-8865-83-2},
}
in EndNote Style
TY - CONF
JO - Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,
TI - FURTHER STUDIES ON VISUAL PERCEPTION FOR PERCEPTUAL ROBOTICS
SN - 978-972-8865-83-2
AU - Ciftcioglu O.
AU - S. Bittermann M.
AU - Sevil Sariyildiz I.
PY - 2007
SP - 468
EP - 477
DO - 10.5220/0001642504680477