Abstract
One important reason to examine the mechanisms of how we see is for the advancement of technology. Robotics as a field has a distinct appeal because its goal is to build fully functioning intelligent systems that can operate robustly in the real world.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Achanta R, Hemami S, Estrada F, Ssstrunk S (2009) Frequency-tuned salient region detection. In: IEEE international conference on computer vision and pattern recognition (CVPR)
Ackerman C, Itti L (2005) Robot steering with spectral image information. IEEE Trans Robot 21:247–251
American Honda Motor Co Inc. (2009). Asimo—the world’s most advanced humanoid robot. http://asimo.honda.com/. Accessed 15 July 2009
Bay H, Tuytelaars T, Gool LV (2006) Surf: speeded up robust features. In: Proceedings of European conference on computer vision (ECCV), pp 404–417
Beeson P, Modayil J, Kuipers B (2010) Factoring the mapping problem: mobile robot map-building in the hybrid spatial semantic hierarchy. Int J Robot Res 29:428–459
Benenson R, Mathias M, Timofte R, Gool LV (2012) Pedestrian detection at 100 frames per second. In: Proceedings of IEEE computer society conference on computer vision and pattern recognition (CVPR). IEEE Computer Society, Providence, RI, USA, pp 290–2910
Biederman I (1982) Do background depth gradients facilitate object identification? Perception 10:573–578
Bruce N, Tsotsos J (2006) Saliency based on information maximization. In: Weiss Y, Scholkopf JPB (eds) Advances in neural information processing systems, vol 18. MIT Press, Cambridge, MA, USA, pp 155–162
Blanco JL, Gonzalez J, Fernndez-Madrigal JA (2006) Consistent observation grouping for generating metric- topological maps that improves robot localization*. In: ICRA. Barcelona, Spain
Chang CK, Siagian C, Itti L (2012) Mobile robot monocular vision navigation based on road region and boundary estimation. In: Proceedings of IEEE/RSJ international conference on intelligent robots and systems (IROS), pp 1043–1050
Chubb C, Sperling G (1988) Drift-balanced random stimuli: a general basis for studying non-Fourier motion perception. J Opt Soc Am 5:1986–2007
Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: CVPR
Epstein R, Stanley D, Harris A, Kanwisher N (2000) The parahippocampal place area: perception, encoding, or memory retrieval? Neuron 23:115–125
Frintrop S, Jensfelt P, Christensen H (2006) Attention landmark selection for visual slam. In: IROS. Beijing
Fox D, Burgard W, Thrun S (1997) The dynamic window approach to collision avoidance. IEEE Robot Autom Mag 4:23–33
Fox D, Burgard W, Dellaert F, Thrun S (1999) Monte carlo localization: efficient position estimation for mobile robots. In: Proceedings of sixteenth national conference on artificial intelligence (AAAI’99)
Gao D, Mahadevan V, Vasconcelos N (2008) On the plausibility of the discriminant center-surround hypothesis for visual saliency. J Vis 8:2301–2311
Goncalves L, Bernardo ED, Benson D, Svedman M, Ostrowski J et al (2005) A visual front-end for simultaneous localization and mapping. In: ICRA, pp 44–49
Henry P, Vollmer C, Ferris B, Fox D (2010) Learning to navigate through crowded environments. In: Proceedings of IEEE international conference on robotics and automation (ICRA), pp 981–986
Hyvrinen A (1999) Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans Neural Netw 10:626–634
Itti L (2012) iLab Neuromorphic Vision C++ Toolkit (iNVT). http://ilab.usc.edu/toolkit/. Accessed 15 Dec 2012
Itti L, Koch C, Niebur E (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 20:1254–1259
Itti L, Dhavale N, Pighin F (2003) Realistic avatar eye and head animation using a neurobiological model of visual attention. In: Bosacchi B, Fogel DB, Bezdek JC (eds) Proceedings of SPIE 48th annual international symposium on optical science and technology, vol 5200. SPIE Press, Bellingham, WA, pp 64–78
Itti L, Koch C (2001) Computational modelling of visual attention. Nat Rev Neurosci 2:194–203
Katsura H, Miura J, Hild M, Shirai Y (2003) A view-based outdoor navigation using object recognition robust to changes of weather and seasons. In: IROS. Las Vegas, NV
Kuipers B (2008) An intellectual history of the spatial semantic hierarchy. In: Jefferies M, Yeap AWK (eds) Robot and cognitive approaches to spatial mapping, vol 99. Springer, pp 21–71
Kuipers B, Modayil J, Beeson P, Macmahon M, Savelli F (2004) Local metrical and global topological maps in the hybrid spatial semantic hierarchy. In: Proceedings of IEEE international conference on robotics and automation (ICRA), pp 4845–4851
Liu T, Yuan Z, Sun J, Wang J, Zheng N et al (2011) Learning to detect a salient object. IEEE Trans Pattern Anal Mach Intell 33:353–367
Li F, VanRullen R, Koch C, Perona P (2002) Rapid natural scene categorization in the near absence of attention. In: Proceedings of National Academy of Science, pp 8378–8383
Lowe D (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60:91–110
Macé MJ, Thorpe SJ, Fabre-Thorpe M (2005) Rapid categorization of achromatic natural scenes: how robust at very low contrasts? Eur J Neurosci 21:2007–2018
Marat S, Phuoc TH, Granjon L, Guyader N, Pellerin D et al (2009) Modelling spatio-temporal saliency to predict gaze direction for short videos. Int J Comput Vis 82:231–243
Marder-Eppstein E, Berger E, Foote T, Gerkey B, Konolige K (2010) The office marathon: robust navigation in an indoor office environment. In: Proceedings of IEEE international conference on robotics and automation (ICRA), pp 300–307
Marder-Eppstein E, Berger E, Foote T, Gerkey B, Konolige K (2011) Kurt Konolige, Eitan Marder-Eppstein, Bhaskara Marthi. In: Proceedings of IEEE international conference on robotics and automation (ICRA), pp 3041–3047
Matsumoto Y, Inaba M, Inoue H (2000) View-based approach to robot navigation. In: IEEE-IROS, pp 1702–1708
McNamara TP (1991) Memory’s view of space. In: Bower GH (ed) The psychology of learning and motivation: advances in research and theory, vol 27. Academic Press, pp 147–186
Milford M, Wyeth G (2008) Mapping a suburb with a single camera using a biologically inspired slam system. IEEE Trans Robot 24:1038–1053
Milford M, Wyeth G (2010) Persistent navigation and mapping using a biologically inspired slam system. Int J Robot Res (IJRR) 29:1131–1153
Montemerlo M, Becker J, Bhat S, Dahlkamp H, Dolgov D et al (2008) Junior: the stanford entry in the urban challenge. J Field Robot 25:569–597
Montemerlo M, Thrun S, Koller D, Wegbreit B (2002) Fastslam: a factored solution to the simultaneous localization and mapping problem. In: AAAI
Moravec H, Elfes A (1985) High resolution maps from wide angle sonar. In: Proceedings of IEEE international conference on robotics and automation (ICRA), vol 2, pp 116–121
Muralidharan K, Vasconcelos N (2006) A biologically plausible network for the computation of orientation dominance. In: Weiss Y, Scholkopf JPB (eds) Advances in neural information processing systems (NIPS), vol 18. MIT Press, Cambridge, MA, USA, pp 155–162
Muralidharan K, Vasconcelos N (2010) On the connections between sift and biological vision. Front Syst Neurosci
Murrieta-Cid R, Parra C, Devy M (2002) Visual navigation in natural environments: from range and color data to a landmark-based model. Auton Robots 13:143–168
Oliva A, Schyns P (1997) Coarse blobs or fine edges? evidence that information diagnosticity changes the perception of complex visual stimuli. Cogn Psychol 34:72–107
Oliva A, Schyns P (2000) Colored diagnostic blobs mediate scene recognition. Cogn Psychol 41:176–210
Oliva A, Torralba A (2001) Modeling the shape of the scene: a holistic representation of the spatial envelope. Int J Comput Vis 42:145–175
Potter MC (1975) Meaning in visual search. Science 187:965–966
Pradeep V, Medioni G, Weiland J (2010) Robot vision for the visually impaired. In: Proceedings of IEEE computer society conference on computer vision and pattern recognition (CVPR). IEEE Computer Society, pp 15–22
Quinlan S, Khatib O (1993) Elastic bands: connecting path planning and control. In: Proceedings of IEEE international conference on robotics and automation (ICRA), pp 802–807
Rahtu E, Kannala J, Salo M, Heikkil J (2010) Segmenting salient objects from images and videos. In: ECCV, pp 366–379
Ramisa A, Tapus A, de Mantaras RL, Toledo R (2008) Mobile robot localization using panoramic vision and combination of local feature region detectors. In: ICRA. Pasadena, CA, pp 538–543
Ranganathan A, Dellaert F (2011) Online probabilistic topological mapping. In: Int J Robot Res (IJRR) 30:755–771
Renniger L, Malik J (2004) When is scene identification just texture recognition? Vis Res 44:2301–2311
Rensink RA (2000) The dynamic representation of scenes. Vis Cogn 7:17–42
Rosin PL (2009) A simple method for detecting salient regions. Pattern Recogn 42:2363–2371
Rutishauser U, Walther D, Koch C, Perona P (2004) Is bottom-up attention useful for object recognition? In: CVPR, vol 2, pp 37–44
Sanocki T, Epstein W (1997) Priming spatial layout of scenes. Psychol Sci 8:374–378
Se S, Lowe DG, Little JJ (2005) Vision-based global localization and mapping for mobile robots. IEEE Trans Robot 21:364–375
Serre T, Wolf L, Bileschi S, Riesenhuber M, Poggio T (2007) Robust object recognition with cortex-like mechanisms. IEEE Trans Pattern Anal Mach Intell 29:411–426
Siagian C, Chang CK, Voorhies R, Itti L (2011) Beobot 2.0: cluster architecture for mobile robotics. J Field Robot 28:278–302
Siagian C, Chang CK, Itti L (2013) Beobot 2.0. http://ilab.usc.edu/beobot2. Accessed 15 Dec 2012
Siagian C, Chang C, Itti L (2013) Mobile robot navigation system in outdoor pedestrian environment using vision-based road recognition. In: Proceedings of IEEE international conference on robotics and automation (ICRA). Both first authors contributed equally
Siagian C, Itti L (2007) Biologically-inspired robotics vision Monte-Carlo localization in the outdoor environment. In: Proceedings of IEEE/RSJ international conference on intelligent robots and systems (IROS)
Siagian C, Itti L (2008) Storing and recalling information for vision localization. In: IEEE international conference on robotics and automation (ICRA). Pasadena, California, pp 1848–1855
Siagian C, Itti L (2007) Rapid biologically-inspired scene classification using features shared with visual attention. IEEE Trans Pattern Anal Mach Intell 29:300–312
Siagian C, Itti L (2009) Biologically inspired mobile robot vision localization. IEEE Trans Robot 25:861–873
Thorpe S, Fize D, Marlot C (1995) Speed of processing in the human visual system. Nature 381:520–522
Thrun S (2011) Google’s driverless car. Talk was viewed at http://www.ted.com/talks/sebastian_thrun_google_s_driverless_car.html. Accessed 1 Sept 2012
Thrun S (1998) Learning metric-topological maps for indoor mobile robot navigation. Artif Intell 99:21–71
Thrun S, Bennewitz M, Burgard W, Cremers A, Dellaert F et al (1999) MINERVA: a second generation mobile tour-guide robot. In: Proceedings of IEEE international conference on robotics and automation (ICRA)
Torralba A (2003) Modeling global scene factors in attention. J Opt Soc Am 20:1407–1418
Torralba A, Murphy KP, Freeman WT, Rubin MA (2003) Context-based vision system for place and object recognition. In: Proceedings of international conference on computer vision (ICCV). Nice, France, pp 1023–1029
Trautman P, Krause A (2010) Unfreezing the robot: navigation in dense, interacting crowds. In: Proceedings of IEEE international conference on intelligent robots and systems (IROS), pp 797–803
Treisman A, Gelade G (1980) A feature-integration theory of attention. Cogn Psychol 12:97–137
Turner RS (1994) In the eye’s mind: vision and the Helmholtz-Hering controversy. Princeton University Press
Tversky B (2003) Navigating by mind and by body. In: Spatial cognition, pp 1–10
Tversky B, Hemenway K (1983) Categories of the environmental scenes. Cogn Psychol 15:121–149
Ulrich I, Nourbakhsh I (2000) Appearance-based place recognition for topological localization. In: Proceedings of IEEE international conference on robotics and automation (ICRA), pp 1023–1029
Ungerleider LG, Mishkin M (1982) Two cortical visual systems. In: Ingle DJ, Goodale MA, Mansfield RJW (eds) Analysis of visual behavior. MIT Press, Cambridge, MA, pp 549–586
Valgren C, Lilienthal AJ (2008) Incremental spectral clustering and seasons: Appearance-based localization in outdoor environments. In: Proceedings of IEEE international conference on robotics and automation (ICRA). Pasadena, CA, pp 1856–1861
Walther D, Koch C (2006) Modeling attention to salient proto-objects. Neural Netw 19:1395–1407
Wang J, Zha H, Cipolla R (2006) Coarse-to-fine vision-based localization by indexing scale-invariant features. IEEE Trans Syst Man Cybern 36:413–422
Willow Garage (2009) PR-2—Wiki. http://pr.willowgarage.com/wiki/PR-2. Accessed 15 July 2009
Wolfe J (1994) Guided search 2.0: a revised model of visual search. Psychon Bull Rev 1:202–238
Zhang L, Tong MH, Marks TK, Shan H, Cottrell GW (2008) Sun: a Bayesian framework for saliency using natural statistics. J Vis 8:231–243
Zhang W, Kosecka J (2005) Localization based on building recognition. In: IEEE workshop on applications for visually impaired, pp 21–28
Acknowledgments
This work was supported by the National Science Foundation (grant numbers CCF-1317433 and CNS-1545089), the Army Research Office (W911NF-12-1-0433), and the Office of Naval Research (N00014-13-1-0563). The authors affirm that the views expressed herein are solely their own, and do not represent the views of the United States government or any agency thereof.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Science+Business Media Singapore
About this chapter
Cite this chapter
Siagian, C., Itti, L. (2017). Impact of Neuroscience in Robotic Vision Localization and Navigation. In: Zhao, Q. (eds) Computational and Cognitive Neuroscience of Vision. Cognitive Science and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-10-0213-7_11
Download citation
DOI: https://doi.org/10.1007/978-981-10-0213-7_11
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-0211-3
Online ISBN: 978-981-10-0213-7
eBook Packages: EngineeringEngineering (R0)