Abstract
Computational models of grounded language learning have been based on the premise that words and concepts are learned simultaneously. Given the mounting cognitive evidence for concept formation in infants, we argue that the availability of pre-lexical concepts (learned from image sequences) leads to considerable computational efficiency in word acquisition. Key to the process is a model of bottom-up visual attention in dynamic scenes. Background learning and foreground segmentation is used to generate robust tracking and detect occlusion events. Trajectories are clustered to obtain motion event concepts. The object concepts (image schemas) are abstracted from the combined appearance and motion data. The set of acquired concepts under visual attentive focus are then correlated with contemporaneous commentary to learn the grounded semantics of words and multi-word phrasal concatenations from the narrative. We demonstrate that even based on a mere half hour of video (of a scene involving many objects and activities), a number of rudimentary concepts can be discovered. When these concepts are associated with unedited English commentary, we find that several words emerge - approximately half the identified concepts from the video are associated with the correct concepts. Thus, the computational model reflects the beginning of language comprehension, based on attentional parsing of the visual data. Finally, the emergence of multi-word phrasal concatenations, a precursor to syntax, is observed where they are more salient referents than single words.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Piaget, J.: The Construction of Reality in the Child. Basic Books, New York (1994)
Fodor, J.A., Lepore, E.: What Can’t Be Evaluated Can’t Be Evaluated, and It Can’t Be Supervalued Either. Journal Of Philosophy 93, 516–536 (1996)
Carey, S.: Knowledge acquisition: Enrichment or conceptual change? In: Carey, S., Gelman, R. (eds.) The Epigenesis of Mind: Essays in Biology and Cognition, pp. 257–291. MIT Press, Cambridge (1999)
Mandler, J.M.: Foundations of Mind. Oxford University Press, New York (2004)
Quin, P., Eimas, P.: The emergence of category representation during infancy: Are separate perceptual and conceptual processes required? Journal of Cognition and development 1, 55–61 (2000)
Jones, S.S., Smith, L.B.: The place of perception in children’s concepts. Cognitive Development 8, 113–139 (1993)
Mandler, J.M.: A synopsis of The foundations of mind: Origins of conceptual thought. Developmental Science 7, 499–505 (2004)
Barsalou, L.W.: Perceptual symbol systems. Behavioral and Brain Sciences 22, 577–609 (1999)
Regier, T.: The Human Semantic Potential: Spatial Language and Constrained Connectionism. Bradford Books (1996)
Roy, D.K., Pentland, A.P.: Learning words from sights and sounds: a computational model. Cognitive Science 26, 113–146 (2002)
Langacker, R.: Foundations of Cognitive Grammar, Descriptive Application, vol. 2. Stanford University Press, Stanford, CA (1991)
Quine, W.V.O.: Word and Object. John Wiley and Sons, New York (1960)
Singh, V.K., Maji, S., Mukerjee, A.: Confidence Based updation of Motion Conspicuity in Dynamic Scenes. In: CRV 2006. Third Canadian Conference on Computer and Robot Vision (2006)
Itti, L., Koch, C.: Computational modeling of visual attention. Nature Reviews Neuroscience 2, 194–203 (2001)
Coldren, J.T., Haaf, R.A.: Priority of processing components of visual stimuli by 6-month-old infants. Infant Behavior and Development 22, 131–135 (1999)
Yu, C., Ballard, D.H.: A Multimodal Learning Interface for Grounding Spoken Language in Sensory Perceptions. ACM Transactions on Applied Perception (2004)
Baillargeon, R., hua Wang, S.: Event categorization in infancy. Trends in Cognitive Sciences 6, 85–93 (2002)
Guha, P., Biswas, A., Mukerjee, A., Venkatesh, K.: Occlusion sequence mining for complex multi-agent activity discovery. In: Proceedings of The Sixth IEEE International Workshop on Visual Surveillance, pp. 33–40 (2006)
Roy, D.: Semiotic schemas: A framework for grounding language in action and perception. Artificial Intelligence 167, 170–205 (2005)
Dominey, P.F., Boucher, J.D.: Learning To Talk About Events From Narrated Video in the Construction Grammar Framework. Artificial Intelligence 167, 31–61 (2005)
Barnard, K., Duygulu, P., Forsyth, D., de Freitas, N., Blei, D.M., Jordan, M.I.: Matching words and pictures. Journal of Machine Learning Research 3, 1107–1135 (2003)
Chang, Y.-H., Morrison, C.T., Kerr, W., Galstyan, A., Cohen, P.R., Beal, C., Amant, R.S., Oates, T.: The Jean System. In: ICDL 2006. International Conference on Development and Learning (2006)
Siskind, J.M.: Grounding the Lexical Semantics of Verbs in Visual Perception using Force Dynamics and Event Logic. J. of Artificial Intelligence Res. 15, 31–90 (2001)
Zivkovic, Z.: Improved adaptive gaussian mixture model for background subtraction. In: Proceedings of the 17th International Conference on Pattern Recognition, vol. 2, pp. 28–31 (2004)
Proesmans, M., Van Gool, L.J., Pauwels, E.J., Osterlinck, A.: Determination of optical flow and its discontinuities using non-linear diffusion. In: Eklundh, J.-O. (ed.) ECCV 1994. LNCS, vol. 801, pp. 295–304. Springer, Heidelberg (1994)
Guha, P., Mukerjee, A., Venkatesh, K.S.: Spatio-temporal Discovery: Appearance + Behavior = Agent. In: Kalra, P., Peleg, S. (eds.) ICVGIP 2006. LNCS, vol. 4338, pp. 516–527. Springer, Heidelberg (2006)
Bloom, P.: How Children Learn the Meanings of Words, pp. 55–87. MIT Press, Cambridge (2000)
Rothenstein, A.L., Tsotsos, J.K.: Attention links sensing to recognition. Image and Vision Computing , 1–13 (2006), doi:10.1016/j.imavis.2005.08.011
Regier, T.: Emergent constraints on word-learning: A computational review. Trends in Cognitive Sciences 7, 263–268 (2003)
Shutts, K., Spelke, E.S.: Straddling the perception-conception boundary. Developmental Science 7, 507–511 (2004)
Stromswold, K.: The cognitive neuroscience of language acquisition. In: Gazzaniga (ed.) The new cognitive neurosciences, pp. 909–932. MIT Press, Cambridge, MA (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Guha, P., Mukerjee, A. (2007). Language Label Learning for Visual Concepts Discovered from Video Sequences. In: Paletta, L., Rome, E. (eds) Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint. WAPCV 2007. Lecture Notes in Computer Science(), vol 4840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77343-6_6
Download citation
DOI: https://doi.org/10.1007/978-3-540-77343-6_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77342-9
Online ISBN: 978-3-540-77343-6
eBook Packages: Computer ScienceComputer Science (R0)