Cognitive Processing

, Volume 9, Issue 4, pp 249–267 | Cite as

On the assessment of landmark salience for human navigation

  • David CaduffEmail author
  • Sabine Timpf


In this paper, we propose a conceptual framework for assessing the salience of landmarks for navigation. Landmark salience is derived as a result of the observer’s point of view, both physical and cognitive, the surrounding environment, and the objects contained therein. This is in contrast to the currently held view that salience is an inherent property of some spatial feature. Salience, in our approach, is expressed as a three-valued Saliency Vector. The components that determine this vector are Perceptual Salience, which defines the exogenous (or passive) potential of an object or region for acquisition of visual attention, Cognitive Salience, which is an endogenous (or active) mode of orienting attention, triggered by informative cues providing advance information about the target location, and Contextual Salience, which is tightly coupled to modality and task to be performed. This separation between voluntary and involuntary direction of visual attention in dependence of the context allows defining a framework that accounts for the interaction between observer, environment, and landmark. We identify the low-level factors that contribute to each type of salience and suggest a probabilistic approach for their integration. Finally, we discuss the implications, consider restrictions, and explore the scope of the framework.


Navigation Landmark Salience Attention Information processing 



The authors would like to thank Urs-Jakob Rueetschi for his valuable input. This work is supported by the Swiss National Science Foundation under grant number 2151-06529101.


  1. Aivar MP, Hayhoe MM, Chizk CL, Mruczek REB (2005) Spatial memory and saccadic targeting in a natural task. J Vis 5(3):177–193PubMedCrossRefGoogle Scholar
  2. Allen GL (1997) From knowledge to words to wayfinding: issues in the preduiction and comprehension of route directions. In: Hirtle SC, Frank AU (eds) Spatial information theory: a theoretical basis for GIS, international conference COSIT ‘97. Springer, Laurel Highlands, pp 363–372CrossRefGoogle Scholar
  3. Anderson ML (2003) Embodied cognition: a field guide. Artif Intell 149(1):91–130CrossRefGoogle Scholar
  4. Appleyard D (1969) Why buildings are known—predictive tool for architects and planners. Environ Behav 1(2):131–156CrossRefGoogle Scholar
  5. Ball K, Owsley C et al (1993) Visual attention problems as a predictor of vehicle crashes in older drivers. Invest Ophthalmol Vis Sci 34:3110–3123PubMedGoogle Scholar
  6. Biederman I (1972) Perceiving real-world scenes. Science 177(4043):77–80PubMedCrossRefGoogle Scholar
  7. Burnett G (2000) “Turn right at the traffic lights”: the requirement for landmarks in vehicle navigation systems. J Navig 53(3):499–510CrossRefGoogle Scholar
  8. Busquets D, Sierra C, De Màntaras RL (2002) A multi-agent approach to fuzzy landmark-based navigation. J Multivalued Log Soft Comput 9:195–220Google Scholar
  9. Busquets D, Sierra C, De Màntaras RL (2003) A multi-agent approach to qualitative landmark-based navigation. Auton Robots 15:129–154CrossRefGoogle Scholar
  10. Caduff D, Timpf S (2005a) The landmark spider: representing landmark knowledge for wayfinding tasks. AAAI 2005 Spring Symposium. AAAI Press, StanfordGoogle Scholar
  11. Caduff D, Timpf S (2005b) The landmark spider: weaving the landmark web. STRC’05—5th Swiss Transport Research Conference. Monte Verità, Switzerland, ETH, CD-ROMGoogle Scholar
  12. Chater N, Tenenbaum JB, Yuille A (2006) Probabilistic Models of Cognition: Conceptual foundations. Trends Cogn Sci 10(7):287–291PubMedCrossRefGoogle Scholar
  13. Couclelis H, Golledge RG, Gale N, Tobler W (1995) Exploring the anchor-point hypothesis of spatial cognition. In: Gaerling T (ed) Urban cognition. Academic, LondonGoogle Scholar
  14. Daniel MP, Denis M (2004) The production of route directions: investigating conditions that favour conciseness in spatial discourse. Appl Cogn Psychol 18(1):57–75CrossRefGoogle Scholar
  15. De Graef P, Lauwereyns J, Verfaillie K (2000) Attentional Orienting and Scene Semantics. Psychological Reports Nr.268. Laboratory of Experimental Psychology, University of Leuven, BelgiumGoogle Scholar
  16. Denis M, Pazzaglia F, Cornoldi C, Bertolo L (1999) Spatial discourse and navigation: an analysis of route directions in the city of Venice. Appl Cogn Sci 13:145–174CrossRefGoogle Scholar
  17. Downs RM, Stea D (1977) Maps in minds:reflections on cognitive mapping. Harper & Row Publishers, New York, p 284Google Scholar
  18. Elias B (2003a) Determination of landmarks and reliability criteria for landmarks. Fifth Workshop on Progress in Automated Map Generalization. ICA Commission on Map Generalization, IGN, ParisGoogle Scholar
  19. Elias B (2003b) Extracting landmarks with data mining methods. In: Kuhn W, Worboys M, Timpf S (eds) International conference on spatial information theory, COSIT 2003. Springer, Kartause Ittingen, pp 375–389Google Scholar
  20. Eriksen CW, St James JD (1986) Visual attention within and around the field of focal attention: a zoom lens model. Percept Psychophys 40(4):225–240PubMedGoogle Scholar
  21. Eriksen CW, Yeh YY (1985) Allocation of attention in the visual field. Exp Psychol Human Percept Perform 11:583–597CrossRefGoogle Scholar
  22. Escrig MT, Toledo F (2000) Autonomous robot navigation using human spatial concepts. Int J Intell Syst 15(3):165–196CrossRefGoogle Scholar
  23. Fontaine S, Denis M (1999) The production of route instructions in underground and urban environments. In: Freksa C, Mark DM (eds) Spatial information theory: cognitive and computational foundations of geographic information science, International Conference COSIT ‘99. Springer, Stade, pp 83–94CrossRefGoogle Scholar
  24. Funes MJ, Lupianez J, Milliken B (2005) The role of spatial attention and other processes on the magnitude and time course of cueing effects. Cogn Process 6(2):98–116PubMedCrossRefGoogle Scholar
  25. Gärling T (1999) Human information processing in sequential spatial choice. In: Golledge RG (ed) Wayfinding behavior: cognitive mapping and other spatial processes. John Hopkins University Press, Baltimore, pp 89–98Google Scholar
  26. Gärling T, Böök A, Lindberg E (1986) Spatial orientation and wayfinding in the designed environment: a conceptual analysis and some suggestions for postoccupancy evaluations. J Archit Plann Res 3:55–64Google Scholar
  27. Galler I (2002) Identifikation von Landmarken in 3D-Stadtmodellen. Institut für Kartographie und Geoinformation. Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, DiplomarbeitGoogle Scholar
  28. Gigerenzer G, Murray DJ (1987) Cognition as intuitive statistics. Erlbaum, HillsdaleGoogle Scholar
  29. Golledge RG (1991) Cognition of physical and built environments. In: Gaerling T, Evans GW (eds) Environment, cognition and action: an integrated approach. Oxford University Press, New YorkGoogle Scholar
  30. Golledge RG (1992) Place recognition and wayfinding—making sense of space. Geoforum 23:199–214CrossRefGoogle Scholar
  31. Golledge RG (1999a) Human wayfinding and cognitive maps. In: Golledge RG (ed) Wayfinding behavior: cognitive mapping and other spatial processes. John Hopkins University Press, Baltimore, pp 5–45Google Scholar
  32. Golledge RG (1999b) Wayfinding behavior: cognitive mapping and other spatial processes. John Hopkins University Press, Baltimore, p 428Google Scholar
  33. Haken H, Portugali J (2003) The face of the city is its information. J Environ Psychol 23(4):385–408CrossRefGoogle Scholar
  34. Hayhoe MM, Shinoda H, Shrivastava A (2000) Attention in Natural Environments. Invest Ophthalmol Vis Sci 41:422–422Google Scholar
  35. Henderson JM, Hollingworth A (1999) High-level Scene Perception. Annu Rev Psychol 50:243–271PubMedCrossRefGoogle Scholar
  36. Hollands MA, Patla AE, Vickers JN (2002) “Look where you’re going!” Gaze Behaviour associated with maintaining and changing the direction of locomotion. Exp Brain Res 143(2):221–230PubMedCrossRefGoogle Scholar
  37. 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(11):1254–1259CrossRefGoogle Scholar
  38. James W (1890) The principles of psychology. Henry Holt & Co, New YorkGoogle Scholar
  39. Janzen G, Turennout MV (2004) Selective neural representation of objects relevant for navigation. Nat Neurosci 7(6):673–677PubMedCrossRefGoogle Scholar
  40. Jensen FV (2001) Bayesian networks and decision graphs. Springer, New YorkGoogle Scholar
  41. Kersten D (2002) Object perception: generative image models and bayesian inference. In: Bülthoff HH et al (eds) Biologically motivated computer vision second international workshop Lecture Notes in Computer Science, vol 2525. Springer, Heidelberg, pp 207–218Google Scholar
  42. Kersten D, Mamassian P, Yuille A (2004) Object Perception as Bayesian inference. Annu Rev Psychol 55:271–304PubMedCrossRefGoogle Scholar
  43. Kersten D, Yuille A (2003) Bayesian models of object perception. Curr Opin Neurobiol 13(2):150–158PubMedCrossRefGoogle Scholar
  44. Klippel A (2004) Wayfinding choremes—conceptualizing wayfinding and route direction elements. KI 18(1):63–64Google Scholar
  45. Klippel A, Richter K-F, Hansen S (2005) Wayfinding choreme maps. In: Bres S, Laurini R (eds) Visual information and information systems, 8th international conference, VISUAL 2005. Springer, Amsterdam, pp 94–108Google Scholar
  46. Klippel A, Winter S (2005) Structural salience of landmarks for route directions. In: Cohn AG, Mark DM (eds) Spatial information theory—COSIT05. Springer, Ellicottville, pp 347–362CrossRefGoogle Scholar
  47. Koch C, Ullman S (1985) Shifts in selective visual-attention—towards the underlying neural circuitry. Human Neurobiol 4(4):219–227Google Scholar
  48. Kosmopoulos DI, Chandrinos KV (2002) Definition and extraction of visual landmarks for indoor robot. Methods and applications of artificial intelligence: second hellenic conference on AI, SETN 2002. Springer, Heidelberg, pp 401–412Google Scholar
  49. Kosslyn SM (1989) Understanding Charts and Graphs. Appl Cogn Psychol 3:185–226CrossRefGoogle Scholar
  50. Kubovy M, Cohen DJ, Hollier J (1999) Feature integration that routinely occurs without focal attention. Psychon Bull Rev 6(2):183–203PubMedGoogle Scholar
  51. Kuipers BJ (1982) The “Map in the Head’’ Metaphor. Environ Behav 14(2):202–220CrossRefGoogle Scholar
  52. Lacroix JPW, Murre JMJ, Postma EO, van den Herik HJ (2006) Modeling recognition memory using the similarity structue of natural input. J Cogn Sci Soc 30(1):121–145Google Scholar
  53. Lee PU, Tappe H, Klippel A (2002) Acquisition of landmark knowledge from static and dynamic presentation of route maps. In: Gray W, Schunn C (eds) Twenty-fourth annual conference of the cognitive science societyGoogle Scholar
  54. Lee Y-C, Lee JD et al (2007) Visual attention in driving: the effects of cognitive load and visual disruption. Hum Factors 49(4):721–733(13)PubMedCrossRefGoogle Scholar
  55. Lewis D (1973) Causality. J Philos 556–567Google Scholar
  56. Lovelace KL, Hegarty M, Montello DR (1999) Elements of good route directions in familiar and unfamiliar environments. In: Freksa C, Mark DM (eds) Spatial information theory: cognitive and computational foundations of geographic information science, international conference COSIT ‘99. Springer, Stade, pp 65–82CrossRefGoogle Scholar
  57. Lynch K (1960) The image of the city. MIT, BostonGoogle Scholar
  58. Marcel A, Dobel C (2005) Structured perceptual input imposes an egocentric frame of reference—pointing, imagery, and spatial self-consciousness. Perception 34(5):429–451PubMedCrossRefGoogle Scholar
  59. May AJ, Ross T, Bayer SH (2003a) Drivers’ information requirements when navigating in an urban environment. J Navig 56(1):89–100CrossRefGoogle Scholar
  60. May AJ, Ross T, Bayer SH, Tarkiainen MJ (2003b) Pedestrian navigation aids: information requirements and design principles. Personal Ubiquitous Comput 7(6):331–338CrossRefGoogle Scholar
  61. Miller GA (1956) The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol Rev 63:81–97PubMedCrossRefGoogle Scholar
  62. Montello DR (1997) The perception and cognition of environmental distance: direct sources of information. In: Hirtle SC, Frank AU (eds) Conference on spatial information theory: a theoretical basis for GIS, COSIT’97. Springer, Laurel Highlands, pp 297–312CrossRefGoogle Scholar
  63. Montello DR (2003) Navigation. In: Shah P, Miyake A (eds) Handbook of visuospatial cognition. Cambridge University Press, Cambridge, pp 257–294Google Scholar
  64. Montello DR, Freundschuh S (2005) Cognition of geographic information. In: Mcmaster RB, Usery EL (eds) A research agenda for geographic information science. CRC Press, Boca RatonGoogle Scholar
  65. Moulin B, Kettani D (1999) Route generation and description using the notion of object’s influence area and spatial conceptual map. Spatial Cogn Comput 1(3):227–259CrossRefGoogle Scholar
  66. Müller NG, Kleinschmid A (2003) Dynamic interaction of object- and space-based attention in retinotopic visual areas. J Neurosci 23:9812–9816PubMedGoogle Scholar
  67. Newell A, Simon HA (1972) Human problem-solving. Prentice Hall, Englewood CliffsGoogle Scholar
  68. Newman EL, Caplan JB, Kirschen MP, Korolev IO, Sekuler R, Kahana MJ (2007) Learning your way around town: how virtual taxicab drivers learn to use both layout and landmark information. Cognition (in press)Google Scholar
  69. Nothegger C (2003) Automatic selection of landmarks. Institute for geoinformation. Technical University of ViennaGoogle Scholar
  70. Nothegger C, Winter S, Raubal M (2004) Computation of the salience of features. Spat Cogn Comput 4:113–136CrossRefGoogle Scholar
  71. Olshausen BA, Anderson CH, Vanessen DC (1992) Computer-simulation of a dynamic routing model of visual-attention. Invest Ophthalmol Vis Sci 33:1263–1263Google Scholar
  72. Parkhurst DJ, Niebur E (2003) Scene content selected by active vision. Spat Vis 16(2):125–154PubMedCrossRefGoogle Scholar
  73. Posner MI (1998) Foundations of cognitive science. MIT, New YorkGoogle Scholar
  74. Presson CC, Montello DR (1988) Points of reference in spatial cognition—stalking the elusive landmark. Br J Dev Psychol 6(4):378–381Google Scholar
  75. Raubal M, Winter S (2002) Enriching wayfinding instructions with local landmarks. In: Egenhofer MJ, Mark DM (eds) Geographic information science. Springer, Berlin, pp 243–259CrossRefGoogle Scholar
  76. Roge J, Pebayle T et al (2005) Useful visual field reduction as a function of age and risk of accident in simulated car driving. Invest Ophthalmol Vis Sci 46:1774–1779PubMedCrossRefGoogle Scholar
  77. Ruz M, Lupianez J (2002) A review of attentional capture: on its automaticity and sensitivity to endogenous control. Psicologica 23(1):283–309Google Scholar
  78. Rüetschi U-J, Caduff D, Schulz F, Wolff A, Timpf S (2006) Routing by landmarks. STRC’06—sixth Swiss transport research conference. Monte Verita, Switzerland, ETH, CD-ROMGoogle Scholar
  79. Schneider W, Shiffrin RM (1977) Controlled and automatic human information-processing.1. Detection, search, and attention. Psychol Rev 84:1–66CrossRefGoogle Scholar
  80. Scholl BJ (2001) Objects and attention: the state of the art. Cognition 80(1):1–46PubMedCrossRefGoogle Scholar
  81. Scholl BJ, Tremoulet PD (2000) Perceptual causality and animacy. Trends Cogn Sci 4(8):299–309PubMedCrossRefGoogle Scholar
  82. Serences JT, Schwarzbach J, Courtney SM, Golay X, Yantis S (2004) Control of object-based attention in human cortex. Cereb Cortex 14(12):1346–1357PubMedCrossRefGoogle Scholar
  83. Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423, 623–656Google Scholar
  84. Shiffrin RM, Schneider W (1977) Controlled and automatic human information-processing.2. Perceptual learning, automatic attending, and a general theory. Psychol Rev 84:127–190CrossRefGoogle Scholar
  85. Shinoda H, Hayhoe MM, Shrivastava A (2001) What controls attention in natural environments? Vis Res 41:3535–3545PubMedCrossRefGoogle Scholar
  86. Siegel AW, White SH (1975) The development of spatial representations of large-scale environments. In: Reese HW (ed) Advances in child development and behavior. Academic, London, pp 9–55Google Scholar
  87. Silva MM, Groeger JA, Bradshaw MF (2006) Attention-memory interactions in scene perception. Spat Vis 19(1):9–19PubMedCrossRefGoogle Scholar
  88. Sorrows ME, Hirtle SC (1999) The nature of landmarks for real and electronic spaces. In: Freksa C, Mark DM (eds) Spatial information theory: cognitive and computational foundations of geographic information science, international conference COSIT ‘99. Springer, Stade, pp, 37–50Google Scholar
  89. Soto D, Blanco MJ (2004) Spatial attention and object-based attention: a comparison within a single task. Vis Res 44(1):69–81PubMedCrossRefGoogle Scholar
  90. Spelke ES (1990) Principles of object perception. Cogn Sci 14(1):29–56CrossRefGoogle Scholar
  91. Staal MA (2004) Stress, cognition, and human performance: a literature review and conceptual framework. Moffett Field, California 94035, National Aeronautics and Space Administration, Ames Research CenterGoogle Scholar
  92. Steck SD, Mochnatzki HF, Mallot HA (2003) The role of geographic slant in virtual environment navigation. In: Freksa C, Brauer W, Habel C, Wender KF (eds) Spatial Cognition III, LNAI 2685, Springer, Heidelberg, pp 62–76CrossRefGoogle Scholar
  93. Stevens Q (2006) The shape of urban experience: a reevaluation of Lynch’s five elements. Environ Plann B Plann Des 33(6):803–823CrossRefGoogle Scholar
  94. Sweller J (1988) Cognitive load during problem solving: effects on learning. Cogn Sci 12(1):257–285CrossRefGoogle Scholar
  95. Tezuka T, Tanaka K (2005) Landmark extraction: a web mining approach. In: Mark DM (ed) Spatial information theory—COSIT05. Springer, Ellicottville, pp 379–398CrossRefGoogle Scholar
  96. Tolman EC (1948) Cognitive maps in rats and men. Psychol Rev 55:189–208PubMedCrossRefGoogle Scholar
  97. Tom A, Denis M (2004) Language and spatial cognition: comparing the roles of landmarks and street names in route instructions. Appl Cogn Psychol 18(9):1213–1230CrossRefGoogle Scholar
  98. Trahanias PE, Velissaris S, Orphanoudakis SC (1999) Visual recognition of workspace landmarks for topological navigation. Auton Robots 7(2):143–158CrossRefGoogle Scholar
  99. Treisman A, Gormican S (1988) Feature analysis in early vision: evidence from search asymmetries. Psychol Rev 95(1):15–48PubMedCrossRefGoogle Scholar
  100. Treisman A, Vieira A, Hayes A (1992) Automaticity and preattentive processing. Am J Psychol 105(2):341–362PubMedCrossRefGoogle Scholar
  101. Treisman AM, Gelade G (1980) Feature-integration theory of attention. Cogn Psychol 12(1):97–136CrossRefGoogle Scholar
  102. Turatto M, Mazza V, Umilta` C (2005) Crossmodal object-based attention: auditory objects affect visual processing. Cognition 96:B55–B64PubMedCrossRefGoogle Scholar
  103. Tversky B (1993) Cognitive maps, cognitive collages, and spatial mental models. In: Frank AU, Campari I (eds) Conference on spatial information theory: COSIT’93. Elba Island, Italy, Springer, Berlin, pp 14–24Google Scholar
  104. Weissensteiner E, Winter S (2004) Landmarks in the Communication of route directions. In: Egenhofer MJ, Miller H, Freksa C (eds) Geographic information science 2004. Lecture Notes in Computer Science, vol 3234. Springer, Berlin, pp 313–326Google Scholar
  105. Werner S, Krieg-Brückner B, Mallot HA, Schweizer K, Freksa C (1997) Spatial cognition: the role of landmark, route, and survey knowledge in human and robot navigation. In: Jarke M, Pasedach K, Pohl K (eds) Informatik aktuell, Springer, Berlin, pp 41–50Google Scholar
  106. Williams LJ (1988) Tunnel vision or general interference? cognitive load and attentional bias are both important. Am J Psychol 101(2):171–191PubMedCrossRefGoogle Scholar
  107. Winter S (2003) Route adaptive selection of salient features. In: Kuhn W, Worboys M, Timpf S (eds) COSIT’03—spatial information theory: foundations of geographic information science. Springer, Heidelberg, pp 320–334Google Scholar
  108. Winter S, Raubal M, Nothegger C (2004) Focalizing measures of salience for route directions. In: Meng L, Zipf A, Reichenbacher T (eds) Map-based mobile services—theories, methods and design implementations. Springer Geosciences, Berlin, pp 127–142Google Scholar
  109. Wolfe JM (1994) Guided Search 2.0—a revised model of visual-search. Psychon Bull Rev 1(2):202–238Google Scholar
  110. Wood S, Cox R, Cheng P (2006) Attention design: eight issues to consider. Comput Hum Behav 22(4):588–602CrossRefGoogle Scholar
  111. Xu YX (2006) Understanding the object benefit in visual short-term memory: the roles of feature proximity and connectedness. Percept Psychophys 68(5):815–828PubMedGoogle Scholar

Copyright information

© Marta Olivetti Belardinelli and Springer-Verlag 2007

Authors and Affiliations

  1. 1.Geographic Information Visualization and Analysis (GIVA), Department of GeographyUniversity of Zurich – IrchelZurichSwitzerland
  2. 2.Department for Computer Science VIUniversity of WuerzburgWuerzburgGermany

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