Abstract
For stereo audio surveillance in complex environment, we proposed a bottom-up audio attention model based on spatial audio cues analysis, and an environment adaptive normalization method. The traditional audio attention models are based on mono audio characters, such as energy, energy peak, or pitch. Their performance is limited by neglecting the spatial information. The spatial cues in audio stream provide additional information for attention analysis. And the dynamic updated background sound can help to reduce the environment effect. The preliminary experiment showed that the proposed model is an effective way to analyzing attention events, which is caused by rapid moving sound source, in stereo audio stream.
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References
James, W.: The Principles of Psychology. Harvard Univ. Press, Cambridge (1890)
Treisman, A., Gelande, G.: A Feature integration theory of attention. Cognitive Psychology 12, 97–136 (1980)
Treisman, A., Gormican, S.: Feature analysis in early vision: evidence from search asymmetries. Psychol. Rev. 95, 15–48 (1988)
Treisman, A.: Perception of features and objects. In: Visual Attention. Oxford Univ. Press, New York (1998)
Posner, M.L.: The Attention System of the Human Brain. Annu. Rev. Neurosci. 13, 25–42 (1990)
Egeth, H.E., Yantis, S.: Visual attention: control, representation, and time course. Annu. Rev. Psychol. 48, 269–297 (1997)
Cui, R., Lu, L., Zhung, H.-J., Cai, L.-H.: Highlight sound effects detection in audio stream. In: ICME (May 2003)
Ma, Y.-F., Hua, X.-S., Lu, L., Zhang, H.-J.: A generic framework of user attention model and its application in video summarization. IEEE Transaction on Multimedia 7, 907–919 (2005)
Huang, Q.-M., Zheng, Y.-J., Jiang, S.-Q., Gao, W.: User Attention Analysis Based Video Summarization and Highlight Ranking. Chinese Journal Of Computers 31(9) (September 2008)
Kalinli, O., Narayanan, S.: A Top-Down Auditory Attention Model for Learning Task Dependent Influences on Prominence Detection in speech. In: ICASSP (March 2008)
Liu, A., Li, J., Zhang, Y., Tang, S., Song, Y., Yang, Z.: Human Attention Model for Action Movie Analysis. In: ICPCA (July 2007)
Evangelopoulos, G., Rapantsikos, K., Potamianos, A., Maragos, P., Zlatintsi, A., Avrithis, Y.: Movie Summarization Based on Audiovisual Saliency Detection. In: ICIP (October 2008)
Faller, C.: Parametric Coding of Spatial Audio. Ph.D Thesis (2004)
Moore, B.C.J.: An Introduction to the Psychology of Hearing, 5th edn. Elsevier Academic Press, Amsterdam (2004)
Roman, N., Wang, D.L.: Binaural Tracking of Multiple Moving Sources. IEEE Transaction on Audio, Speech, and Language Processing 16(4), 728–739 (2008)
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© 2009 Springer-Verlag Berlin Heidelberg
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Hang, B., Hu, R., Yang, Y., Ma, Y., Chang, J. (2009). Surveillance Audio Attention Model Based on Spatial Audio Cues. In: Muneesawang, P., Wu, F., Kumazawa, I., Roeksabutr, A., Liao, M., Tang, X. (eds) Advances in Multimedia Information Processing - PCM 2009. PCM 2009. Lecture Notes in Computer Science, vol 5879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10467-1_81
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DOI: https://doi.org/10.1007/978-3-642-10467-1_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10466-4
Online ISBN: 978-3-642-10467-1
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