Special Issue - Dynamic Textures in Video Two-dimensional textures in images have been extensively studied in the past. On the other hand, there is comparatively limited research on three-dimensional dynamic textures that exhibit certain time-varying properties in video. Many scenes that could loosely be referred to as static often contain cyclostationary processes: meaning that there is significant structure in the correlations between observations across time. A tree swaying in the wind or a wave lapping on a beach is not just a collection of randomly shuffled appearances, but a physical system that has characteristic responses associated with its dynamics. The examples of such dynamic phenomena can be extended to fire, smoke, sea, waves, clouds, fog, crowds in public places and sports events, human movements, and even to cast shadows. It is known that dynamic textures, especially for outdoor scenes, cause major problems in motion detection and analysis tasks. Besides, they drastically decrease the coding efficiency of video encoders although they do not contain any useful and discriminative information. They complicate motion based object recognition methods. By segmenting and excluding dynamic textures, the robustness of the moving object detection and action identification can be improved. Other practical applications include detection of certain types of dynamic textures, realistic rendering and compact visualization of dynamic textures, and efficient retrieval of dynamic video in multimedia databases. The objective of this special issue is to provide a comprehensive overview of theoretical and practical aspects as well as collate and disseminate the state of the art research results on dynamic textures. In this context, high quality contributions are solicited on, but not restricted to, the following topics: Dynamic texture detection and classification Spatiotemporal features for dynamic texture characterization Image and video based modeling, rendering, and synthesis of dynamic textures Adaptive dynamic textures for background modeling Segmentation of scenes containing dynamic textures Motion estimation over dynamic texture regions Efficient coding of dynamic texture regions Content retrieval by dynamic textures in multimedia databases Action representation and recognition by dynamic textures Visualization of dynamic textures Dynamic texture databases and benchmarking Crowd detection and crowd behavior analysis in video Applications for smoke, flame, water, wave, liquid detection Applications in biomedical, surveillance, and consumer video Machine Vision and Applications accepts high-quality technical contributions which are within its aims and scope in both long and short paper formats. Long papers may not be over 30 manuscript pages in length (12 point type, double-spaced, 5 cm margins (2 inch) on one side of the paper only) including figures, references, acknowledgements, footnotes, tables, and captions. All papers should be written in English. Further guidelines can be viewed at http://www.springerlink.com/content/100522/. Deadline for manuscript submission: August 1, 2008 Final accepted manuscripts due: September 1, 2009 Anticipated issue publication: December 2009 Submitting Your Manuscript Machine Vision and Applications employs a completely automated submission and review process. To submit a manuscript, please visit http://mc.manuscriptcentral.com/mva. If you are new to Manuscript Central, please use the Create Account link in the top right corner of the page to create a new account. Once you have created an account you will have access to your Author Dashboard. More information can be found regarding use of Manuscript Central in the Help section of the website. Machine Vision and Applications publishes high-quality technical contributions in machine vision research and development. Specifically, the editors encourage submittals in all applications and engineering aspects of image-related computing. In particular, original contributions dealing with scientific, commercial, industrial, military, and biomedical applications of machine vision, are all within the scope of the journal. Particular emphasis is placed on engineering and technology aspects of image processing and computer vision.