Call for Papers Computer Vision and Image Understanding Journal (CVIU) Special Issue on Spatial Coherence in Visual Motion Analysis Guest Editors W. James MacLean, University of Toronto, Canada Nikos Paragios, Ecole Nationale des Ponts et Chausses, France David Fleet, University of Toronto, Canada Motion analysis is a central problem in computer vision, and the past two decades have seen important advances in this field. However, visual motion is still often considered on a pixel-by-pixel basis, even though this ignores the fact that image regions corresponding to a single object usually undergo motion that is highly correlated. This independence is often an explicit assumption that is made when developing computational models. Models in which such independence is not assumed, for example Markov Random Fields, are typically computationally expensive, and therefore many times are not the model of choice. It must be noted that an implicit assumption of spatial coherence exists in motion models employing region based estimates of quantities such as image gradients. Further, it is often of interest to accurately measure the boundaries of moving regions. In the case of articulated motion, especially human motion, discovering motion boundaries is non-trivial but an important task nonetheless. Early approaches focused on measuring motion of either the boundaries or the interior, but seldom both in unison. In the case of identifying and tracking independent object motion, such a united approach may be essential, given the possibly small region subtended by the tracked object(s). Another related problem is identifying and grouping multiple disconnected regions moving with similar motions, such as a flock of geese. In the past several years attempts have been made to include spatial coherence terms into algorithms for 2- and 3-D motion recovery, as well as motion boundary estimation. This special issue will examine the state-of-the-art in techniques for integrating spatial coherence constraints during motion analysis on image sequences. While a broad range of topics will be considered, papers submitted must make a significant contribution to furthering ability to take advantage of spatial coherence to produce more accurate and reliable motion estimates. Topics for submitted papers include (but are not limited to): o Bayesian models of spatial coherence o Belief Propagation o Generative Models o Markov random field techniques o Optic Flow o Recovery of motion boundaries o Active contours & boundary tracking o Motion boundary interpretation and occlusion/disocclusion modeling o Articulated Motion o Independent Object Motion o Visual Tracking o Layered motion models o Region segmentation & Motion-based grouping o Perceptual grouping of pixel motions o Spatial coherence models for transparency o Spatial coherence in biological vision o Human motion analysis o Use of contextual information in applying spatial coherence o Local-Parallel computation models for motion o Graph-Based Methods for Motion Segmentation All submitted papers will be reviewed according to the guidelines and standards of the Computer Vision and Image Understanding Journal. We prefer that the authors submit electronic versions of their papers in postscript or pdf to W. James MacLean (maclean+cviu@eecg.toronto.edu). If electronic submission is not possible then five paper copies may be sent to: Prof. W. James MacLean, Edward S. Rogers Sr. Dept of Electrical & Computer Engineering, University of Toronto 10 King's College Road, Toronto, ON M5S 3G4 Canada Deadlines Manuscript submission February 28, 2005 Reviews sent to authors June 30, 2005 Submission of revised manuscripts August 31, 2005 Final accept/reject notification September 30, 2005 Publication date: Fourth quarter 2005 For further information please contact W. James MacLean ( mailto:maclean+cviu@eecg.toronto.edu ).