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Detecting Regions of Dynamic Texture

  • Conference paper
Scale Space and Variational Methods in Computer Vision (SSVM 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4485))

Abstract

Motion estimation is usually based on the brightness constancy assumption. This assumption holds well for rigid objects with a Lambertian surface, but it is less appropriate for fluid and gaseous materials. For these materials a variant of this assumption, which we call the brightness conservation assumption should be employed. Under this assumption an object’s brightness can diffuse to its neighborhood. We propose a method for detecting regions of dynamic texture in image sequences. Segmentation into regions of static and dynamic texture is achieved by using a level set scheme. The level set function separates the images into areas obeying brightness constancy and those which obey brightness conservation. Experimental results on challenging image sequences demonstrate the success of the segmentation scheme and validate the model.

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Authors and Affiliations

  1. School of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel

    Tomer Amiaz & Nahum Kiryati

  2. Computer and Automation Research Institute, Budapest, Hungary

    Sándor Fazekas & Dmitry Chetverikov

Authors
  1. Tomer Amiaz
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  2. Sándor Fazekas
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  3. Dmitry Chetverikov
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  4. Nahum Kiryati
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Fiorella Sgallari Almerico Murli Nikos Paragios

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Amiaz, T., Fazekas, S., Chetverikov, D., Kiryati, N. (2007). Detecting Regions of Dynamic Texture. In: Sgallari, F., Murli, A., Paragios, N. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2007. Lecture Notes in Computer Science, vol 4485. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72823-8_73

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  • DOI: https://doi.org/10.1007/978-3-540-72823-8_73

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72822-1

  • Online ISBN: 978-3-540-72823-8

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